In [ ]:
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import matplotlib.ticker as mticker
In [ ]:
# Assuming the file is in the root of your Google Drive's "My Drive" folder
file_path = "https://github.com/sachinr-2911/python_for_datascience/raw/main/Financial_Data_Total.csv"

try:
  df = pd.read_csv(file_path)
  print("File loaded successfully!")
  # Now you can work with the DataFrame 'df'
  # For example, to display the first 5 rows:
  print(df.head())

except FileNotFoundError:
  print(f"Error: File not found at {file_path}. Please check the file path.")
except pd.errors.ParserError:
  print(f"Error: Could not parse the file at {file_path}. Please check the file format.")
except Exception as e:
  print(f"An unexpected error occurred: {e}")
File loaded successfully!
   year fiscalDateEnding_balance reportedCurrency_balance  totalAssets  \
0  2017               12/31/2017                      USD     3421.566   
1  2018               12/31/2018                      USD     2714.106   
2  2019               12/31/2019                      USD     4011.924   
3  2020               12/31/2020                      USD     5024.238   
4  2021               12/31/2021                      USD     7536.306   

   totalCurrentAssets  cashAndCashEquivalentsAtCarryingValue  \
0         2700.857000                                334.063   
1         2063.077000                                387.149   
2         3164.303002                                520.317   
3         3883.593001                                545.618   
4         7041.011000                               1993.809   

   cashAndShortTermInvestments  inventory  currentNetReceivables  \
0                     2043.039   0.000000                279.473   
1                     1279.063   0.000000                354.965   
2                     2112.805   0.000002                492.194   
3                     2537.540   0.000001                744.288   
4                     3886.085   0.000000               1068.873   

   totalNonCurrentAssets  ...  NetWorkingCapital/Sales  avgReceivables  \
0               1077.472  ...              1513.619000             NaN   
1               1081.778  ...               585.077000        317.2190   
2               1422.938  ...               887.310002        423.5795   
3               1855.763  ...              1093.486001        618.2410   
4               2682.304  ...              2087.375000        906.5805   

   DebtorDays  AvgPayables  CreditorDays  totalDebt  debtRatioToCapital  \
0         NaN          NaN           NaN     32.066           -0.006934   
1   98.594744       51.035     15.862173        NaN                 NaN   
2   89.103246       38.881      8.178921    933.955           -0.155349   
3   93.548109       59.397      8.987558   1716.246           -0.277922   
4   80.671376       98.595      8.773401   2305.483           -0.385599   

   CummulativeCashflowFromOperations  CummulativeCNetProfits  Innovation %  
0                           -734.667               -3445.066      1.860555  
1                          -1424.591               -4700.977      0.657541  
2                          -1729.549               -5734.637      0.509186  
3                          -1897.193               -6679.476      0.456660  
4                          -1604.313               -7167.431      0.381649  

[5 rows x 123 columns]
In [ ]:
df.head()
Out[ ]:
year fiscalDateEnding_balance reportedCurrency_balance totalAssets totalCurrentAssets cashAndCashEquivalentsAtCarryingValue cashAndShortTermInvestments inventory currentNetReceivables totalNonCurrentAssets ... NetWorkingCapital/Sales avgReceivables DebtorDays AvgPayables CreditorDays totalDebt debtRatioToCapital CummulativeCashflowFromOperations CummulativeCNetProfits Innovation %
0 2017 12/31/2017 USD 3421.566 2700.857000 334.063 2043.039 0.000000 279.473 1077.472 ... 1513.619000 NaN NaN NaN NaN 32.066 -0.006934 -734.667 -3445.066 1.860555
1 2018 12/31/2018 USD 2714.106 2063.077000 387.149 1279.063 0.000000 354.965 1081.778 ... 585.077000 317.2190 98.594744 51.035 15.862173 NaN NaN -1424.591 -4700.977 0.657541
2 2019 12/31/2019 USD 4011.924 3164.303002 520.317 2112.805 0.000002 492.194 1422.938 ... 887.310002 423.5795 89.103246 38.881 8.178921 933.955 -0.155349 -1729.549 -5734.637 0.509186
3 2020 12/31/2020 USD 5024.238 3883.593001 545.618 2537.540 0.000001 744.288 1855.763 ... 1093.486001 618.2410 93.548109 59.397 8.987558 1716.246 -0.277922 -1897.193 -6679.476 0.456660
4 2021 12/31/2021 USD 7536.306 7041.011000 1993.809 3886.085 0.000000 1068.873 2682.304 ... 2087.375000 906.5805 80.671376 98.595 8.773401 2305.483 -0.385599 -1604.313 -7167.431 0.381649

5 rows × 123 columns

In [ ]:
onetry:
  # Print all 123 columns
  print(df.columns.tolist())

except NameError:
  print("Error: 'df' DataFrame not found. Please make sure you've loaded the CSV file correctly.")
except AttributeError:
    print("Error: 'df' does not have a 'columns' attribute. Make sure it's a Pandas DataFrame.")
except Exception as e:
  print(f"An unexpected error occurred: {e}")
['year', 'fiscalDateEnding_balance', 'reportedCurrency_balance', 'totalAssets', 'totalCurrentAssets', 'cashAndCashEquivalentsAtCarryingValue', 'cashAndShortTermInvestments', 'inventory', 'currentNetReceivables', 'totalNonCurrentAssets', 'propertyPlantEquipment', 'accumulatedDepreciationAmortizationPPE', 'intangibleAssets', 'intangibleAssetsExcludingGoodwill', 'goodwill', 'investments', 'longTermInvestments', 'shortTermInvestments', 'otherCurrentAssets', 'otherNonCurrentAssets', 'totalLiabilities', 'totalCurrentLiabilities', 'currentAccountsPayable', 'deferredRevenue', 'currentDebt', 'shortTermDebt', 'totalNonCurrentLiabilities', 'capitalLeaseObligations', 'longTermDebt', 'currentLongTermDebt', 'longTermDebtNoncurrent', 'shortLongTermDebtTotal', 'otherCurrentLiabilities', 'otherNonCurrentLiabilities', 'totalShareholderEquity', 'treasuryStock', 'retainedEarnings', 'commonStock', 'commonStockSharesOutstanding', 'fiscalDateEnding_income', 'reportedCurrency_income', 'grossProfit', 'totalRevenue', 'costOfRevenue', 'costofGoodsAndServicesSold', 'operatingIncome', 'sellingGeneralAndAdministrative', 'researchAndDevelopment', 'operatingExpenses', 'investmentIncomeNet', 'netInterestIncome', 'interestIncome', 'interestExpense', 'nonInterestIncome', 'otherNonOperatingIncome', 'depreciation', 'depreciationAndAmortization', 'incomeBeforeTax', 'incomeTaxExpense', 'interestAndDebtExpense', 'netIncomeFromContinuingOperations', 'comprehensiveIncomeNetOfTax', 'ebit', 'ebitda', 'netIncome', 'fiscalDateEnding', 'reportedCurrency', 'operatingCashflow', 'paymentsForOperatingActivities', 'proceedsFromOperatingActivities', 'changeInOperatingLiabilities', 'changeInOperatingAssets', 'depreciationDepletionAndAmortization', 'capitalExpenditures', 'changeInReceivables', 'changeInInventory', 'profitLoss', 'cashflowFromInvestment', 'cashflowFromFinancing', 'proceedsFromRepaymentsOfShortTermDebt', 'paymentsForRepurchaseOfCommonStock', 'paymentsForRepurchaseOfEquity', 'paymentsForRepurchaseOfPreferredStock', 'dividendPayout', 'dividendPayoutCommonStock', 'dividendPayoutPreferredStock', 'proceedsFromIssuanceOfCommonStock', 'proceedsFromIssuanceOfLongTermDebtAndCapitalSecuritiesNet', 'proceedsFromIssuanceOfPreferredStock', 'proceedsFromRepurchaseOfEquity', 'proceedsFromSaleOfTreasuryStock', 'changeInCashAndCashEquivalents', 'changeInExchangeRate', 'netIncome_cashflow', 'Current Ratio', 'Quick Ratio', 'Debt Equity Ratio', 'ROE', 'ROA', 'Dividend Yield', 'EBITDA', 'Adjusted Close', 'EPS', 'Revenue per Share', 'Book Value per Share', 'P/E Ratio', 'P/S Ratio', 'P/B Ratio', 'Company', 'SalesGrowth', 'OperatingProfitMargin', 'netProfitMargin', 'NetWorkingCapital', 'NetWorkingCapital/Sales', 'avgReceivables', 'DebtorDays', 'AvgPayables', 'CreditorDays', 'totalDebt', 'debtRatioToCapital', 'CummulativeCashflowFromOperations', 'CummulativeCNetProfits', 'Innovation %']
In [ ]:
import pandas as pd

# Define the columns and their descriptions
columns_data = [
    ("year", "The year of the financial data.", "General Information"),
    ("fiscalDateEnding_balance", "The date when the balance sheet data ends.", "Balance Sheet"),
    ("reportedCurrency_balance", "Currency in which balance sheet data is reported (e.g., USD, EUR).", "Balance Sheet"),
    ("totalAssets", "Total value of everything the company owns (e.g., cash, buildings, equipment).", "Balance Sheet"),
    ("totalCurrentAssets", "Assets that can be quickly converted into cash, typically within a year.", "Balance Sheet"),
    ("cashAndCashEquivalentsAtCarryingValue", "Cash and short-term investments that are as good as cash.", "Balance Sheet"),
    ("cashAndShortTermInvestments", "Cash and investments that can be easily converted into cash.", "Balance Sheet"),
    ("inventory", "The value of goods the company plans to sell in the near future.", "Balance Sheet"),
    ("currentNetReceivables", "Money that customers owe to the company but has not been paid yet.", "Balance Sheet"),
    ("totalNonCurrentAssets", "Long-term assets that cannot be quickly converted to cash.", "Balance Sheet"),
    ("propertyPlantEquipment", "Physical assets like buildings or machinery used for business operations.", "Balance Sheet"),
    ("accumulatedDepreciationAmortizationPPE", "The total reduction in the value of physical assets due to wear and tear.", "Balance Sheet"),
    ("intangibleAssets", "Non-physical assets like patents, trademarks, or copyrights.", "Balance Sheet"),
    ("goodwill", "Extra value paid when acquiring a company, beyond its tangible assets.", "Balance Sheet"),
    ("investments", "Money invested in other companies or ventures.", "Balance Sheet"),
    ("longTermInvestments", "Investments that are expected to be held for more than a year.", "Balance Sheet"),
    ("shortTermInvestments", "Investments that can be easily turned into cash within a year.", "Balance Sheet"),
    ("otherCurrentAssets", "Miscellaneous assets that are expected to be converted into cash soon.", "Balance Sheet"),
    ("otherNonCurrentAssets", "Other long-term assets not categorized elsewhere.", "Balance Sheet"),
    ("totalLiabilities", "Total amount of money the company owes to others.", "Balance Sheet"),
    ("totalCurrentLiabilities", "Debts or obligations that must be settled within a year.", "Balance Sheet"),
    ("currentAccountsPayable", "Money the company owes to suppliers or creditors.", "Balance Sheet"),
    ("deferredRevenue", "Payments received for goods or services that have not yet been delivered.", "Balance Sheet"),
    ("currentDebt", "Short-term borrowings that need to be paid within a year.", "Balance Sheet"),
    ("shortTermDebt", "Loans or debts that are due within a year.", "Balance Sheet"),
    ("totalNonCurrentLiabilities", "Long-term debts or obligations that are not due soon.", "Balance Sheet"),
    ("capitalLeaseObligations", "Long-term rental agreements for the use of assets.", "Balance Sheet"),
    ("longTermDebt", "Debt that is due for payment after more than a year.", "Balance Sheet"),
    ("treasuryStock", "The companys own stock that it has repurchased but not canceled.", "Balance Sheet"),
    ("retainedEarnings", "Profits the company has kept instead of paying them out as dividends.", "Balance Sheet"),
    ("commonStock", "Shares issued to shareholders in exchange for ownership in the company.", "Balance Sheet"),
    ("commonStockSharesOutstanding", "The total number of shares currently held by shareholders.", "Balance Sheet"),
    ("fiscalDateEnding_income", "The date when the income statement data ends.", "Income Statement"),
    ("reportedCurrency_income", "Currency in which income statement data is reported.", "Income Statement"),
    ("grossProfit", "Revenue minus the cost of goods sold.", "Income Statement"),
    ("totalRevenue", "Total income generated from all business activities.", "Income Statement"),
    ("costOfRevenue", "Costs directly tied to producing goods and services.", "Income Statement"),
    ("costofGoodsAndServicesSold", "Cost of producing the goods or services the company sells.", "Income Statement"),
    ("operatingIncome", "Profit from the companys main business operations.", "Income Statement"),
    ("sellingGeneralAndAdministrative", "Costs related to selling and managing the business.", "Income Statement"),
    ("researchAndDevelopment", "Expenditures for developing new products or services.", "Income Statement"),
    ("operatingExpenses", "Total expenses from running the business operations.", "Income Statement"),
    ("investmentIncomeNet", "Income earned from investments.", "Income Statement"),
    ("netInterestIncome", "Income earned from interest, minus interest expenses.", "Income Statement"),
    ("interestIncome", "Money earned from lending or investing.", "Income Statement"),
    ("interestExpense", "The cost of borrowing money.", "Income Statement"),
    ("nonInterestIncome", "Income earned without interest, like fees or royalties.", "Income Statement"),
    ("otherNonOperatingIncome", "Income from activities not related to the core business.", "Income Statement"),
    ("depreciation", "The reduction in value of physical assets over time.", "Income Statement"),
    ("depreciationAndAmortization", "Total depreciation of physical assets and amortization of intangible assets.", "Income Statement"),
    ("incomeBeforeTax", "Income before any taxes are deducted.", "Income Statement"),
    ("incomeTaxExpense", "Taxes the company owes based on its income.", "Income Statement"),
    ("interestAndDebtExpense", "Total costs related to borrowing and interest payments.", "Income Statement"),
    ("netIncomeFromContinuingOperations", "Profit from ongoing business activities, after expenses and taxes.", "Income Statement"),
    ("comprehensiveIncomeNetOfTax", "Total income after taxes, including unusual gains or losses.", "Income Statement"),
    ("ebit", "Earnings before interest and taxes; a measure of operating profit.", "Income Statement"),
    ("ebitda", "Earnings before interest, taxes, depreciation, and amortization; shows operating profitability.", "Income Statement"),
    ("netIncome", "The companys total profit after all expenses and taxes.", "Income Statement"),
    ("fiscalDateEnding", "The date when the cash flow data ends.", "Cash Flow Statement"),
    ("reportedCurrency", "Currency in which cash flow data is reported.", "Cash Flow Statement"),
    ("operatingCashflow", "Cash generated by the company from its main business activities.", "Cash Flow Statement"),
    ("paymentsForOperatingActivities", "Cash used for the companys core operations.", "Cash Flow Statement"),
    ("proceedsFromOperatingActivities", "Cash received from the companys core operations.", "Cash Flow Statement"),
    ("changeInOperatingLiabilities", "The increase or decrease in the company's short-term obligations.", "Cash Flow Statement"),
    ("changeInOperatingAssets", "The increase or decrease in the companys short-term assets.", "Cash Flow Statement"),
    ("depreciationDepletionAndAmortization", "Cash flow impact from reducing the value of physical and intangible assets.", "Cash Flow Statement"),
    ("capitalExpenditures", "Cash spent on buying or improving physical assets like buildings or equipment.", "Cash Flow Statement"),
    ("changeInReceivables", "Changes in money owed to the company by customers.", "Cash Flow Statement"),
    ("changeInInventory", "Changes in the amount of inventory held by the company.", "Cash Flow Statement"),
    ("profitLoss", "The net result of the companys financial activities; profit or loss.", "Cash Flow Statement"),
    ("cashflowFromInvestment", "Cash flow related to buying or selling investments.", "Cash Flow Statement"),
    ("cashflowFromFinancing", "Cash flow from borrowing money, issuing shares, or paying dividends.", "Cash Flow Statement"),
    ("proceedsFromRepaymentsOfShortTermDebt", "Money received from repaying short-term borrowings.", "Cash Flow Statement"),
    ("paymentsForRepurchaseOfCommonStock", "Cash spent to buy back the companys own shares.", "Cash Flow Statement"),
    ("paymentsForRepurchaseOfEquity", "Cash spent to repurchase shares or ownership.", "Cash Flow Statement"),
    ("paymentsForRepurchaseOfPreferredStock", "Cash used to buy back preferred stock from shareholders.", "Cash Flow Statement"),
    ("dividendPayout", "Cash paid to shareholders as dividends.", "Cash Flow Statement"),
    ("dividendPayoutCommonStock", "Dividends paid on common shares.", "Cash Flow Statement"),
    ("dividendPayoutPreferredStock", "Dividends paid on preferred shares.", "Cash Flow Statement"),
    ("proceedsFromIssuanceOfCommonStock", "Cash received from issuing new common shares.", "Cash Flow Statement"),
    ("proceedsFromIssuanceOfLongTermDebtAndCapitalSecuritiesNet", "Cash received from issuing long-term debt or securities.", "Cash Flow Statement"),
    ("proceedsFromIssuanceOfPreferredStock", "Cash raised from issuing preferred stock.", "Cash Flow Statement"),
    ("proceedsFromRepurchaseOfEquity", "Cash received from repurchasing equity.", "Cash Flow Statement"),
    ("proceedsFromSaleOfTreasuryStock", "Cash from selling stock that was repurchased earlier.", "Cash Flow Statement"),
    ("changeInCashAndCashEquivalents", "Change in cash and cash equivalents from one period to the next.", "Cash Flow Statement"),
    ("changeInExchangeRate", "Change in cash due to currency exchange rates.", "Cash Flow Statement"),
    ("cashAndCashEquivalentsPeriodEnd", "Amount of cash and equivalents at the end of the period.", "Cash Flow Statement"),
]

# Convert the data into a DataFrame for better viewing
df_data_dict = pd.DataFrame(columns_data, columns=["Column", "Description", "Section"])
In [ ]:
print(df_data_dict.to_string())
                                                       Column                                                                                      Description              Section
0                                                        year                                                                  The year of the financial data.  General Information
1                                    fiscalDateEnding_balance                                                       The date when the balance sheet data ends.        Balance Sheet
2                                    reportedCurrency_balance                               Currency in which balance sheet data is reported (e.g., USD, EUR).        Balance Sheet
3                                                 totalAssets                   Total value of everything the company owns (e.g., cash, buildings, equipment).        Balance Sheet
4                                          totalCurrentAssets                         Assets that can be quickly converted into cash, typically within a year.        Balance Sheet
5                       cashAndCashEquivalentsAtCarryingValue                                        Cash and short-term investments that are as good as cash.        Balance Sheet
6                                 cashAndShortTermInvestments                                     Cash and investments that can be easily converted into cash.        Balance Sheet
7                                                   inventory                                 The value of goods the company plans to sell in the near future.        Balance Sheet
8                                       currentNetReceivables                               Money that customers owe to the company but has not been paid yet.        Balance Sheet
9                                       totalNonCurrentAssets                                       Long-term assets that cannot be quickly converted to cash.        Balance Sheet
10                                     propertyPlantEquipment                        Physical assets like buildings or machinery used for business operations.        Balance Sheet
11                     accumulatedDepreciationAmortizationPPE                        The total reduction in the value of physical assets due to wear and tear.        Balance Sheet
12                                           intangibleAssets                                     Non-physical assets like patents, trademarks, or copyrights.        Balance Sheet
13                                                   goodwill                           Extra value paid when acquiring a company, beyond its tangible assets.        Balance Sheet
14                                                investments                                                   Money invested in other companies or ventures.        Balance Sheet
15                                        longTermInvestments                                   Investments that are expected to be held for more than a year.        Balance Sheet
16                                       shortTermInvestments                                   Investments that can be easily turned into cash within a year.        Balance Sheet
17                                         otherCurrentAssets                           Miscellaneous assets that are expected to be converted into cash soon.        Balance Sheet
18                                      otherNonCurrentAssets                                                Other long-term assets not categorized elsewhere.        Balance Sheet
19                                           totalLiabilities                                                Total amount of money the company owes to others.        Balance Sheet
20                                    totalCurrentLiabilities                                         Debts or obligations that must be settled within a year.        Balance Sheet
21                                     currentAccountsPayable                                                Money the company owes to suppliers or creditors.        Balance Sheet
22                                            deferredRevenue                        Payments received for goods or services that have not yet been delivered.        Balance Sheet
23                                                currentDebt                                        Short-term borrowings that need to be paid within a year.        Balance Sheet
24                                              shortTermDebt                                                       Loans or debts that are due within a year.        Balance Sheet
25                                 totalNonCurrentLiabilities                                            Long-term debts or obligations that are not due soon.        Balance Sheet
26                                    capitalLeaseObligations                                               Long-term rental agreements for the use of assets.        Balance Sheet
27                                               longTermDebt                                             Debt that is due for payment after more than a year.        Balance Sheet
28                                              treasuryStock                                The companys own stock that it has repurchased but not canceled.        Balance Sheet
29                                           retainedEarnings                            Profits the company has kept instead of paying them out as dividends.        Balance Sheet
30                                                commonStock                          Shares issued to shareholders in exchange for ownership in the company.        Balance Sheet
31                               commonStockSharesOutstanding                                       The total number of shares currently held by shareholders.        Balance Sheet
32                                    fiscalDateEnding_income                                                    The date when the income statement data ends.     Income Statement
33                                    reportedCurrency_income                                             Currency in which income statement data is reported.     Income Statement
34                                                grossProfit                                                            Revenue minus the cost of goods sold.     Income Statement
35                                               totalRevenue                                             Total income generated from all business activities.     Income Statement
36                                              costOfRevenue                                             Costs directly tied to producing goods and services.     Income Statement
37                                 costofGoodsAndServicesSold                                       Cost of producing the goods or services the company sells.     Income Statement
38                                            operatingIncome                                              Profit from the companys main business operations.     Income Statement
39                            sellingGeneralAndAdministrative                                              Costs related to selling and managing the business.     Income Statement
40                                     researchAndDevelopment                                            Expenditures for developing new products or services.     Income Statement
41                                          operatingExpenses                                             Total expenses from running the business operations.     Income Statement
42                                        investmentIncomeNet                                                                  Income earned from investments.     Income Statement
43                                          netInterestIncome                                            Income earned from interest, minus interest expenses.     Income Statement
44                                             interestIncome                                                          Money earned from lending or investing.     Income Statement
45                                            interestExpense                                                                     The cost of borrowing money.     Income Statement
46                                          nonInterestIncome                                          Income earned without interest, like fees or royalties.     Income Statement
47                                    otherNonOperatingIncome                                         Income from activities not related to the core business.     Income Statement
48                                               depreciation                                             The reduction in value of physical assets over time.     Income Statement
49                                depreciationAndAmortization                     Total depreciation of physical assets and amortization of intangible assets.     Income Statement
50                                            incomeBeforeTax                                                            Income before any taxes are deducted.     Income Statement
51                                           incomeTaxExpense                                                      Taxes the company owes based on its income.     Income Statement
52                                     interestAndDebtExpense                                          Total costs related to borrowing and interest payments.     Income Statement
53                          netIncomeFromContinuingOperations                               Profit from ongoing business activities, after expenses and taxes.     Income Statement
54                                comprehensiveIncomeNetOfTax                                     Total income after taxes, including unusual gains or losses.     Income Statement
55                                                       ebit                               Earnings before interest and taxes; a measure of operating profit.     Income Statement
56                                                     ebitda  Earnings before interest, taxes, depreciation, and amortization; shows operating profitability.     Income Statement
57                                                  netIncome                                         The companys total profit after all expenses and taxes.     Income Statement
58                                           fiscalDateEnding                                                           The date when the cash flow data ends.  Cash Flow Statement
59                                           reportedCurrency                                                    Currency in which cash flow data is reported.  Cash Flow Statement
60                                          operatingCashflow                                 Cash generated by the company from its main business activities.  Cash Flow Statement
61                             paymentsForOperatingActivities                                                     Cash used for the companys core operations.  Cash Flow Statement
62                            proceedsFromOperatingActivities                                                Cash received from the companys core operations.  Cash Flow Statement
63                               changeInOperatingLiabilities                                The increase or decrease in the company's short-term obligations.  Cash Flow Statement
64                                    changeInOperatingAssets                                     The increase or decrease in the companys short-term assets.  Cash Flow Statement
65                       depreciationDepletionAndAmortization                      Cash flow impact from reducing the value of physical and intangible assets.  Cash Flow Statement
66                                        capitalExpenditures                   Cash spent on buying or improving physical assets like buildings or equipment.  Cash Flow Statement
67                                        changeInReceivables                                               Changes in money owed to the company by customers.  Cash Flow Statement
68                                          changeInInventory                                          Changes in the amount of inventory held by the company.  Cash Flow Statement
69                                                 profitLoss                            The net result of the companys financial activities; profit or loss.  Cash Flow Statement
70                                     cashflowFromInvestment                                              Cash flow related to buying or selling investments.  Cash Flow Statement
71                                      cashflowFromFinancing                             Cash flow from borrowing money, issuing shares, or paying dividends.  Cash Flow Statement
72                      proceedsFromRepaymentsOfShortTermDebt                                              Money received from repaying short-term borrowings.  Cash Flow Statement
73                         paymentsForRepurchaseOfCommonStock                                                 Cash spent to buy back the companys own shares.  Cash Flow Statement
74                              paymentsForRepurchaseOfEquity                                                    Cash spent to repurchase shares or ownership.  Cash Flow Statement
75                      paymentsForRepurchaseOfPreferredStock                                         Cash used to buy back preferred stock from shareholders.  Cash Flow Statement
76                                             dividendPayout                                                          Cash paid to shareholders as dividends.  Cash Flow Statement
77                                  dividendPayoutCommonStock                                                                 Dividends paid on common shares.  Cash Flow Statement
78                               dividendPayoutPreferredStock                                                              Dividends paid on preferred shares.  Cash Flow Statement
79                          proceedsFromIssuanceOfCommonStock                                                    Cash received from issuing new common shares.  Cash Flow Statement
80  proceedsFromIssuanceOfLongTermDebtAndCapitalSecuritiesNet                                         Cash received from issuing long-term debt or securities.  Cash Flow Statement
81                       proceedsFromIssuanceOfPreferredStock                                                        Cash raised from issuing preferred stock.  Cash Flow Statement
82                             proceedsFromRepurchaseOfEquity                                                          Cash received from repurchasing equity.  Cash Flow Statement
83                            proceedsFromSaleOfTreasuryStock                                            Cash from selling stock that was repurchased earlier.  Cash Flow Statement
84                             changeInCashAndCashEquivalents                                 Change in cash and cash equivalents from one period to the next.  Cash Flow Statement
85                                       changeInExchangeRate                                                   Change in cash due to currency exchange rates.  Cash Flow Statement
86                            cashAndCashEquivalentsPeriodEnd                                         Amount of cash and equivalents at the end of the period.  Cash Flow Statement
In [ ]:
pd.set_option('display.max_rows', None)
correlation_num = df.select_dtypes(include=['int64','float64'])
correlation_matrix = correlation_num.corr()
correlation_matrix
Out[ ]:
year totalAssets totalCurrentAssets cashAndCashEquivalentsAtCarryingValue cashAndShortTermInvestments inventory currentNetReceivables totalNonCurrentAssets propertyPlantEquipment accumulatedDepreciationAmortizationPPE intangibleAssets intangibleAssetsExcludingGoodwill goodwill investments longTermInvestments shortTermInvestments otherCurrentAssets otherNonCurrentAssets totalLiabilities totalCurrentLiabilities currentAccountsPayable deferredRevenue currentDebt shortTermDebt totalNonCurrentLiabilities capitalLeaseObligations longTermDebt currentLongTermDebt longTermDebtNoncurrent shortLongTermDebtTotal otherCurrentLiabilities otherNonCurrentLiabilities totalShareholderEquity treasuryStock retainedEarnings commonStock commonStockSharesOutstanding grossProfit totalRevenue costOfRevenue costofGoodsAndServicesSold operatingIncome sellingGeneralAndAdministrative researchAndDevelopment operatingExpenses investmentIncomeNet netInterestIncome interestIncome interestExpense nonInterestIncome otherNonOperatingIncome depreciation depreciationAndAmortization incomeBeforeTax incomeTaxExpense interestAndDebtExpense netIncomeFromContinuingOperations comprehensiveIncomeNetOfTax ebit ebitda netIncome operatingCashflow paymentsForOperatingActivities proceedsFromOperatingActivities changeInOperatingLiabilities changeInOperatingAssets depreciationDepletionAndAmortization capitalExpenditures changeInReceivables changeInInventory profitLoss cashflowFromInvestment cashflowFromFinancing proceedsFromRepaymentsOfShortTermDebt paymentsForRepurchaseOfCommonStock paymentsForRepurchaseOfEquity paymentsForRepurchaseOfPreferredStock dividendPayout dividendPayoutCommonStock dividendPayoutPreferredStock proceedsFromIssuanceOfCommonStock proceedsFromIssuanceOfLongTermDebtAndCapitalSecuritiesNet proceedsFromIssuanceOfPreferredStock proceedsFromRepurchaseOfEquity proceedsFromSaleOfTreasuryStock changeInCashAndCashEquivalents changeInExchangeRate netIncome_cashflow Current Ratio Quick Ratio Debt Equity Ratio ROE ROA Dividend Yield EBITDA Adjusted Close EPS Revenue per Share Book Value per Share P/E Ratio P/S Ratio P/B Ratio SalesGrowth OperatingProfitMargin netProfitMargin NetWorkingCapital NetWorkingCapital/Sales avgReceivables DebtorDays AvgPayables CreditorDays totalDebt debtRatioToCapital CummulativeCashflowFromOperations CummulativeCNetProfits Innovation %
year 1.000000 0.462363 0.441787 0.465632 0.300566 0.271143 0.505255 0.189363 0.620760 0.637695 0.439428 0.085310 0.485065 0.238218 -0.008793 0.203217 0.415180 0.472808 0.411760 0.418024 0.247724 0.224468 0.254958 0.076011 0.343934 0.252524 0.333751 0.484995 0.250159 0.205381 0.487111 0.189234 0.313628 0.847258 0.203581 0.205741 0.299276 0.542231 0.443668 0.341991 0.329702 0.458929 0.471890 0.660126 0.572448 0.274194 -0.330298 0.153526 0.341442 0.601514 0.083645 0.837099 0.373598 0.459875 0.267627 0.331050 0.487005 0.482524 0.461268 0.463889 0.486785 0.464251 0.469564 -0.525097 -0.181573 0.341367 0.617497 0.559602 0.177161 0.238220 0.487075 0.189613 -0.565953 -0.024913 0.474387 0.471407 NaN 0.675077 0.204936 NaN -0.091109 -0.200287 NaN -0.524978 NaN 0.015864 -0.051566 0.486785 -0.186072 -0.183761 0.406854 0.176203 -0.042308 -0.034417 0.459507 0.619985 0.523601 0.590446 0.386363 -0.202693 0.223491 0.483250 -0.292571 -0.054517 -0.026086 0.169821 -0.352709 0.482942 0.335574 0.219959 -0.057388 0.322557 -0.008602 0.571003 0.549695 0.133758
totalAssets 0.462363 1.000000 0.928594 0.782023 0.727352 0.712756 0.931723 0.805916 0.745727 0.926630 0.670912 0.603921 0.666583 0.806861 0.483442 0.607401 0.890356 0.631464 0.865611 0.854887 0.657000 0.486229 0.576849 0.457609 0.806133 0.494971 0.704016 0.618235 0.667144 0.630319 0.765688 0.615727 0.715564 0.996896 0.547825 0.736581 0.571772 0.928666 0.899559 0.809477 0.794146 0.893051 0.824803 0.761047 0.801023 0.888126 -0.685633 0.743119 0.688226 0.779621 -0.210226 0.906458 0.725002 0.903459 0.789921 0.684985 0.892916 0.895726 0.907585 0.914932 0.896009 0.919670 0.692238 -0.735130 0.202065 0.621824 0.917406 0.721040 0.453022 0.066160 0.892865 -0.249629 -0.772204 0.041203 0.752656 0.758621 NaN 0.845764 0.679996 NaN -0.215399 0.427393 NaN -0.778382 NaN 0.075760 -0.095922 0.896009 -0.645494 -0.646035 0.480217 0.651823 0.521554 0.509612 0.893930 0.444224 0.530160 0.575447 0.217919 -0.116059 -0.324591 0.308822 -0.572309 0.356645 0.368798 0.384305 -0.698806 0.921047 -0.095922 0.646040 0.549122 0.701198 0.633108 0.846114 0.812154 -0.465968
totalCurrentAssets 0.441787 0.928594 1.000000 0.713350 0.909953 0.628378 0.851580 0.589745 0.733759 0.864388 0.759506 0.636017 0.760250 0.679603 0.141169 0.807218 0.763667 0.541019 0.768401 0.736028 0.455766 0.543094 0.393563 0.289314 0.710284 0.531461 0.602595 0.521710 0.548739 0.476080 0.666028 0.436170 0.715612 -0.999161 0.491602 0.837034 0.545138 0.855436 0.758806 0.639835 0.614049 0.756111 0.875038 0.770091 0.838546 0.755203 -0.650651 0.615986 0.654350 0.617093 -0.026464 0.848317 0.603809 0.771185 0.646043 0.649979 0.765822 0.776318 0.777133 0.785145 0.771272 0.793247 0.659251 -0.473282 0.265362 0.502647 0.923207 0.699908 0.327541 0.162022 0.765691 -0.207110 -0.674925 -0.186963 0.574776 0.594165 NaN 0.739469 0.626104 NaN -0.132384 0.198928 NaN -0.635343 NaN 0.106340 -0.088464 0.771272 -0.565394 -0.566438 0.400622 0.573412 0.495835 0.298163 0.755620 0.473965 0.518473 0.551699 0.264833 -0.105042 -0.288216 0.259441 -0.585901 0.368910 0.380704 0.626416 -0.466024 0.847208 0.065373 0.446181 0.354440 0.590457 0.585365 0.738138 0.702548 -0.441973
cashAndCashEquivalentsAtCarryingValue 0.465632 0.782023 0.713350 1.000000 0.439937 0.575277 0.754246 0.612681 0.647123 0.846385 0.432654 0.208653 0.457339 0.735749 0.461702 0.223147 0.684240 0.668114 0.709769 0.679849 0.651693 0.178323 0.485957 0.316223 0.660629 0.161526 0.646034 0.693227 0.573618 0.618416 0.705539 0.659466 0.511622 -0.807003 0.411573 0.370650 0.432202 0.776796 0.797385 0.742429 0.743747 0.763553 0.603288 0.686437 0.642792 0.778847 -0.558858 0.681448 0.561989 0.753330 -0.107422 0.733337 0.702857 0.770306 0.633788 0.558381 0.774740 0.786831 0.772446 0.778985 0.773023 0.777753 0.696764 -0.522050 -0.073476 0.414730 0.761470 0.591005 0.224904 0.117308 0.774620 0.053674 -0.741448 -0.235453 0.721029 0.732318 NaN 0.482579 0.451032 NaN -0.161948 0.085689 NaN -0.754588 NaN 0.286307 -0.338316 0.773023 -0.490547 -0.490269 0.470647 0.628844 0.475234 0.446283 0.774528 0.504771 0.566032 0.608029 0.306903 -0.087545 -0.267715 0.371152 -0.409876 0.301516 0.316172 0.268602 -0.648861 0.752960 -0.265706 0.666544 0.525144 0.634922 0.554440 0.770253 0.748444 -0.372228
cashAndShortTermInvestments 0.300566 0.727352 0.909953 0.439937 1.000000 0.348780 0.576781 0.329935 0.648997 0.601743 0.736233 0.617361 0.735285 0.404733 -0.215042 0.965648 0.483113 0.207789 0.487973 0.434539 0.087635 0.514986 0.014023 0.081903 0.460054 0.549540 0.318276 0.152698 0.241328 0.172461 0.402439 0.087656 0.721719 -0.183357 0.499352 0.788570 0.330252 0.616823 0.449243 0.301815 0.276703 0.448635 0.812920 0.647293 0.752450 0.491234 -0.435231 0.406172 0.443611 0.270753 0.083655 0.614761 0.333252 0.470582 0.383691 0.434527 0.464909 0.479876 0.476376 0.486905 0.473039 0.518842 0.426205 -0.392973 0.324273 0.285166 0.781126 0.647419 0.193528 0.265702 0.464742 -0.316265 -0.358327 -0.268323 0.170551 0.218496 NaN 0.310418 0.427611 NaN -0.090430 0.230802 NaN -0.304579 NaN 0.074908 -0.058220 0.473039 -0.400039 -0.401273 0.108469 0.297484 0.390649 0.059834 0.445262 0.378606 0.443999 0.467818 0.341411 -0.091058 -0.267222 -0.007296 -0.492418 0.340783 0.349220 0.840850 -0.083956 0.553345 0.160295 0.059528 0.042868 0.304671 0.377986 0.419053 0.375667 -0.366640
inventory 0.271143 0.712756 0.628378 0.575277 0.348780 1.000000 0.839753 0.624283 0.191423 0.794063 0.496067 0.679314 0.445138 0.794761 0.603515 0.246495 0.782665 0.868547 0.918348 0.888025 0.883558 0.397805 0.859214 0.608295 0.866536 0.273158 0.872023 0.823044 0.866526 0.797990 0.651409 0.859095 0.089931 0.999338 -0.080783 0.648290 0.761355 0.693223 0.808844 0.850874 0.821039 0.798757 0.409702 0.360294 0.385603 0.798712 -0.856790 0.666563 0.856806 0.772286 -0.217189 0.474887 0.609793 0.788509 0.733866 0.856605 0.768547 0.769816 0.797547 0.789872 0.771857 0.726010 0.631277 NaN 0.342463 0.629891 0.570839 0.141401 0.306193 -0.200470 0.768613 0.089491 -0.779338 0.116536 0.764632 0.772874 NaN 0.701916 0.822414 NaN -0.209305 0.197483 NaN -0.781054 NaN 0.026576 -0.022142 0.771857 -0.584171 -0.586383 0.837589 0.782384 0.366931 0.588728 0.794780 0.193450 0.073515 0.093439 -0.335298 -0.062558 -0.149271 0.688089 -0.482406 0.203771 0.207253 -0.096348 -0.808813 0.836302 0.059706 0.879892 0.781859 0.871843 0.752837 0.869189 0.876469 -0.363416
currentNetReceivables 0.505255 0.931723 0.851580 0.754246 0.576781 0.839753 1.000000 0.745834 0.626149 0.972992 0.709373 0.624378 0.711557 0.829052 0.493043 0.452604 0.915368 0.820011 0.923500 0.939323 0.786462 0.471238 0.700523 0.470018 0.825667 0.406351 0.767273 0.758398 0.734582 0.687921 0.842151 0.723974 0.502743 0.874078 0.318588 0.759485 0.720095 0.936037 0.946325 0.887715 0.867449 0.945606 0.744555 0.716183 0.735394 0.856471 -0.775613 0.709159 0.776799 0.872248 -0.146425 0.760773 0.781245 0.948434 0.809860 0.775201 0.943662 0.943389 0.952905 0.956693 0.945040 0.924838 0.746864 -0.577255 0.190978 0.697635 0.845687 0.550538 0.471389 -0.021414 0.943640 -0.017701 -0.910221 0.066016 0.878504 0.881633 NaN 0.772265 0.727233 NaN -0.119055 0.084855 NaN -0.887768 NaN 0.049030 -0.076163 0.945040 -0.618268 -0.619012 0.688236 0.767738 0.465279 0.456491 0.948209 0.418537 0.421750 0.462106 0.035306 -0.093285 -0.214688 0.557089 -0.548718 0.281743 0.294362 0.173569 -0.829363 0.994369 0.022533 0.782791 0.604378 0.761685 0.661336 0.947662 0.935087 -0.397697
totalNonCurrentAssets 0.189363 0.805916 0.589745 0.612681 0.329935 0.624283 0.745834 1.000000 0.429864 0.699564 0.263946 0.420965 0.230277 0.743970 0.817369 0.215311 0.809009 0.510367 0.742267 0.764128 0.738434 0.298200 0.606431 0.512873 0.723037 0.441260 0.606464 0.483231 0.601917 0.645111 0.656226 0.694574 0.512736 0.700234 0.498072 0.446489 0.419483 0.702571 0.818852 0.842481 0.833651 0.800703 0.456471 0.383482 0.412149 0.780964 -0.495074 0.786807 0.500507 0.848231 -0.519191 0.711656 0.735043 0.805118 0.804796 0.494609 0.775783 0.776283 0.805427 0.820462 0.775450 0.816055 0.429629 -0.778769 0.045208 0.489712 0.588569 0.441007 0.374809 -0.090620 0.775802 -0.345622 -0.597043 0.191875 0.630093 0.645592 NaN 0.518286 0.617822 NaN -0.278875 0.629448 NaN -0.674654 NaN 0.079687 -0.142104 0.775450 -0.592706 -0.593015 0.421756 0.551530 0.421258 0.734524 0.811964 0.119701 0.226360 0.262199 -0.072300 -0.103840 -0.338157 0.229976 -0.387436 0.255578 0.262041 -0.010627 -0.783325 0.711364 -0.289130 0.717178 0.711749 0.613433 0.502481 0.690847 0.667879 -0.435961
propertyPlantEquipment 0.620760 0.745727 0.733759 0.647123 0.648997 0.191423 0.626149 0.429864 1.000000 0.759995 0.567521 0.240149 0.615908 0.370780 -0.070010 0.539450 0.545338 0.278821 0.392883 0.430203 0.148692 0.261577 -0.094996 0.021192 0.292263 0.319272 0.160165 0.157088 0.041130 0.085178 0.623051 0.080050 0.885293 0.731262 0.767830 0.457535 0.256293 0.790546 0.607391 0.400148 0.409731 0.607300 0.882441 0.939075 0.923446 0.530162 -0.192781 0.381565 0.207193 0.537092 0.102330 0.828313 0.513031 0.624117 0.439330 0.192181 0.643723 0.640395 0.618141 0.637961 0.643256 0.690988 0.518570 -0.611305 -0.073882 0.434685 0.818621 0.957730 0.391860 0.394361 0.643645 -0.248822 -0.539206 -0.044083 0.446930 0.470264 NaN 0.577639 0.134031 NaN 0.000851 -0.182428 NaN -0.525672 NaN 0.031149 -0.145453 0.643256 -0.363597 -0.362219 0.031808 0.286808 0.358429 -0.014600 0.610363 0.591956 0.801115 0.884384 0.703739 -0.084247 -0.225170 0.037356 -0.344250 0.251070 0.269678 0.586144 -0.338429 0.592216 -0.130206 0.112368 -0.057098 0.152722 0.170774 0.529690 0.490601 -0.221678
accumulatedDepreciationAmortizationPPE 0.637695 0.926630 0.864388 0.846385 0.601743 0.794063 0.972992 0.699564 0.759995 1.000000 0.747694 0.613323 0.762670 0.792987 0.383946 0.460438 0.901278 0.811584 0.900662 0.916535 0.721104 0.483502 0.605868 0.420214 0.806963 0.417652 0.755827 0.734723 0.706566 0.673207 0.840277 0.679763 0.541225 0.838693 0.350804 0.742709 0.728166 0.948407 0.923025 0.858110 0.835080 0.924569 0.786074 0.859643 0.824611 0.829459 -0.762602 0.683462 0.765165 0.896243 -0.072331 0.894659 0.786865 0.925893 0.734735 0.762268 0.934267 0.933910 0.930646 0.934683 0.935606 0.906616 0.814135 -0.579698 0.089957 0.666445 0.902902 0.686671 0.395753 -0.013761 0.934280 0.003221 -0.919496 -0.016601 0.880697 0.884881 NaN 0.803258 0.690076 NaN -0.073156 -0.046197 NaN -0.892606 NaN -0.002813 -0.096120 0.935606 -0.573240 -0.573398 0.659551 0.718115 0.434585 0.382291 0.928676 0.638268 0.683721 0.732139 0.202361 -0.074726 -0.138799 0.562690 -0.531659 0.259172 0.273949 0.233810 -0.787381 0.977365 0.015507 0.717430 0.520780 0.744249 0.630927 0.947629 0.929165 -0.344192
intangibleAssets 0.439428 0.670912 0.759506 0.432654 0.736233 0.496067 0.709373 0.263946 0.567521 0.747694 1.000000 0.826087 0.994052 0.291776 -0.308428 0.716399 0.686067 0.783649 0.662771 0.683788 0.121889 0.846771 0.084080 0.049714 0.573832 0.917006 0.472153 0.487381 0.468597 0.215592 0.213786 0.103079 0.522858 -0.878816 0.269849 0.713638 0.518725 0.657278 0.443991 0.288471 0.168144 0.603438 0.644537 0.574098 0.639579 0.430740 -0.708969 0.281853 0.707107 0.546748 0.045561 0.632174 0.179828 0.591926 0.378491 0.708383 0.607382 0.598102 0.605541 0.580991 0.614238 0.553240 0.642195 -0.790454 0.233543 0.480429 0.758371 0.590428 0.393215 -0.072877 0.607292 -0.198305 -0.623632 -0.459935 0.276127 0.314752 NaN 0.660852 0.644922 NaN 0.018459 -0.322412 NaN -0.370638 NaN 0.052607 -0.099176 0.614238 -0.222895 -0.223619 0.231462 0.445955 0.337427 0.174925 0.571173 0.680694 0.488403 0.406675 0.333253 -0.058784 0.062153 0.232148 -0.325488 0.314110 0.311968 0.534774 -0.166754 0.695159 0.253995 0.096495 -0.000026 0.444327 0.405336 0.726763 0.733121 -0.248755
intangibleAssetsExcludingGoodwill 0.085310 0.603921 0.636017 0.208653 0.617361 0.679314 0.624378 0.420965 0.240149 0.613323 0.826087 1.000000 0.765734 0.383962 -0.001349 0.631125 0.682191 0.691627 0.725971 0.705727 0.375132 0.820242 0.375285 0.271044 0.697052 0.920702 0.614997 0.512395 0.660275 0.410752 0.063507 0.347008 0.333950 -0.880362 0.115188 0.715868 0.547425 0.488204 0.415075 0.412662 0.273903 0.542615 0.418213 0.234415 0.361470 0.508470 -0.779820 0.297026 0.777611 0.349018 -0.224483 0.431656 0.145471 0.522112 0.462944 0.779312 0.497668 0.501565 0.539878 0.519320 0.509689 0.488514 0.487830 -0.772105 0.457007 0.365951 0.508635 0.281166 0.292924 -0.335741 0.497509 -0.357814 -0.403045 -0.293029 0.129549 0.174758 NaN 0.706715 0.819425 NaN -0.148183 0.318240 NaN -0.228379 NaN 0.040161 -0.147744 0.509689 -0.307532 -0.309476 0.420207 0.461661 0.305158 0.465298 0.514555 0.315841 0.109557 0.026085 -0.089497 -0.031267 -0.016392 0.172698 -0.321821 0.293320 0.279936 0.321786 -0.254668 0.600529 0.196750 0.363634 0.372077 0.599004 0.544921 0.626308 0.641407 -0.328557
goodwill 0.485065 0.666583 0.760250 0.457339 0.735285 0.445138 0.711557 0.230277 0.615908 0.762670 0.994052 0.765734 1.000000 0.271539 -0.352873 0.710170 0.667489 0.772289 0.628692 0.658702 0.070548 0.817877 0.023222 0.003103 0.528978 0.901343 0.428524 0.469784 0.414320 0.169580 0.244081 0.054512 0.548435 0.880779 0.293560 0.699446 0.516603 0.676927 0.444748 0.261701 0.150387 0.602194 0.676903 0.625391 0.680616 0.403495 -0.666459 0.283949 0.665924 0.584603 0.099048 0.660783 0.188094 0.592149 0.352332 0.665872 0.615264 0.605631 0.604329 0.581261 0.620988 0.553078 0.653007 -0.791711 0.191344 0.490430 0.777651 0.629744 0.406296 -0.025644 0.615191 -0.164222 -0.653151 -0.467514 0.302223 0.338694 NaN 0.636456 0.590063 NaN 0.044313 -0.325138 NaN -0.393233 NaN 0.046330 -0.083692 0.620988 -0.205154 -0.205627 0.187802 0.430781 0.334727 0.116790 0.571138 0.718175 0.542015 0.464509 0.397991 -0.062788 0.068012 0.229352 -0.320837 0.308519 0.308577 0.558075 -0.152507 0.698446 0.256462 0.043089 -0.069049 0.399062 0.367208 0.726723 0.732399 -0.227889
investments 0.238218 0.806861 0.679603 0.735749 0.404733 0.794761 0.829052 0.743970 0.370780 0.792987 0.291776 0.383962 0.271539 1.000000 0.763583 0.297077 0.734337 0.684044 0.859897 0.799732 0.837448 0.161264 0.829806 0.588378 0.827764 0.075130 0.837633 0.757333 0.798491 0.857749 0.752774 0.853911 0.345060 0.682233 0.257475 0.528125 0.599503 0.718074 0.862235 0.876656 0.893207 0.772811 0.512570 0.450217 0.474370 0.911404 -0.736710 0.850893 0.738718 0.787460 -0.209075 0.591109 0.754024 0.777752 0.688563 0.736318 0.766813 0.770530 0.786165 0.800814 0.769130 0.766555 0.612993 0.111154 0.264613 0.508971 0.651926 0.333787 0.323310 -0.072280 0.766818 0.036630 -0.784889 -0.047684 0.819633 0.826206 NaN 0.488102 0.638486 NaN -0.276931 0.294328 NaN -0.837823 NaN 0.120644 -0.116743 0.769130 -0.612948 -0.614164 0.657865 0.695300 0.436979 0.597521 0.789369 0.081577 0.198444 0.267337 -0.122376 -0.102781 -0.381742 0.391747 -0.517043 0.257388 0.270078 0.075944 -0.786215 0.819542 -0.129469 0.836979 0.751630 0.838379 0.702377 0.785369 0.766615 -0.442395
longTermInvestments -0.008793 0.483442 0.141169 0.461702 -0.215042 0.603515 0.493043 0.817369 -0.070010 0.383946 -0.308428 -0.001349 -0.352873 0.763583 1.000000 -0.311616 0.540962 0.467485 0.625373 0.585881 0.832400 -0.150455 0.775938 0.616287 0.642490 -0.269203 0.641051 0.508503 0.658034 0.793115 0.487486 0.832871 -0.009579 NaN 0.090037 -0.023911 0.285416 0.349559 0.655928 0.779339 0.804846 0.567768 -0.077019 -0.060027 -0.096293 0.726179 -0.421410 0.759452 0.427964 0.692213 -0.515727 0.235625 0.569729 0.566995 0.629411 0.421410 0.527657 0.527419 0.571040 0.577621 0.525808 0.544098 0.270376 NaN -0.016568 0.346758 0.183563 -0.055815 0.231962 -0.135673 0.527723 -0.054572 -0.442933 0.229159 0.562511 0.579338 NaN 0.258796 0.452770 NaN -0.507331 0.651388 NaN -0.591274 NaN 0.113237 0.028250 0.525808 -0.624704 -0.624473 0.527779 0.506462 0.282390 0.748437 0.584368 -0.187575 -0.121326 -0.085372 -0.360214 0.063916 -0.287170 0.274859 -0.190356 0.160492 0.159774 -0.460940 -0.765649 0.445668 -0.419598 0.809553 0.832129 0.658500 0.548967 0.517107 0.509996 -0.329281
shortTermInvestments 0.203217 0.607401 0.807218 0.223147 0.965648 0.246495 0.452604 0.215311 0.539450 0.460438 0.716399 0.631125 0.710170 0.297077 -0.311616 1.000000 0.359679 0.054506 0.370139 0.317074 -0.046564 0.521023 -0.074176 0.043708 0.352660 0.570435 0.202699 0.008978 0.130869 0.058345 0.260617 -0.049543 0.656336 0.418525 0.441852 0.769187 0.241613 0.473900 0.294248 0.148863 0.125087 0.297820 0.728327 0.521932 0.649677 0.362552 -0.363298 0.320887 0.372944 0.107901 0.099086 0.425678 0.193741 0.320551 0.260781 0.362659 0.312946 0.324550 0.327294 0.336695 0.322358 0.369994 0.291291 -0.310108 0.419007 0.227307 0.665061 0.553777 0.203159 0.230974 0.312798 -0.329214 -0.219790 -0.194053 0.014505 0.064563 NaN 0.173689 0.367559 NaN -0.064463 0.245550 NaN -0.157702 NaN 0.027615 -0.027784 0.322358 -0.319628 -0.321070 0.003588 0.161622 0.303456 -0.025028 0.292195 0.264886 0.328370 0.344741 0.279674 -0.078795 -0.233662 -0.118137 -0.428576 0.294791 0.300479 0.824682 0.056890 0.416937 0.248336 -0.083743 -0.060601 0.192558 0.280584 0.265333 0.221967 -0.310360
otherCurrentAssets 0.415180 0.890356 0.763667 0.684240 0.483113 0.782665 0.915368 0.809009 0.545338 0.901278 0.686067 0.682191 0.667489 0.734337 0.540962 0.359679 1.000000 0.744990 0.899257 0.937981 0.765734 0.623739 0.666521 0.524235 0.836408 0.616279 0.747145 0.710454 0.725704 0.695274 0.674423 0.720178 0.457273 0.940556 0.300467 0.688021 0.658377 0.860425 0.872680 0.851087 0.804385 0.916894 0.628351 0.578930 0.612571 0.798460 -0.748334 0.591943 0.750334 0.841110 -0.255152 0.783259 0.668064 0.911096 0.794354 0.747958 0.902948 0.891194 0.916991 0.910307 0.904096 0.886751 0.683660 -0.762737 0.134320 0.640720 0.771069 0.515350 0.427758 -0.220074 0.902937 -0.145443 -0.793303 0.213944 0.749519 0.759630 NaN 0.819865 0.807822 NaN -0.113339 0.312161 NaN -0.774009 NaN -0.004509 -0.157673 0.904096 -0.632858 -0.633427 0.621212 0.708286 0.451710 0.600168 0.908397 0.427452 0.370112 0.370856 -0.034659 -0.079249 -0.168087 0.467586 -0.475378 0.279520 0.287034 0.045535 -0.811595 0.903008 -0.021829 0.751865 0.667694 0.746889 0.637893 0.884799 0.869284 -0.403912
otherNonCurrentAssets 0.472808 0.631464 0.541019 0.668114 0.207789 0.868547 0.820011 0.510367 0.278821 0.811584 0.783649 0.691627 0.772289 0.684044 0.467485 0.054506 0.744990 1.000000 0.848029 0.865888 0.871428 0.326641 0.763865 0.478979 0.756125 0.161628 0.784005 0.868864 0.770241 0.707604 0.720334 0.816822 0.034121 -0.611789 -0.116401 0.488127 0.742670 0.720681 0.812807 0.842316 0.812831 0.823113 0.377750 0.468613 0.419000 0.696372 -0.822858 0.517258 0.824518 0.862619 -0.124342 0.504993 0.640480 0.809080 0.684134 0.822829 0.807452 0.810226 0.814402 0.804648 0.807504 0.717861 0.744149 -0.667630 0.042591 0.611237 0.559837 0.181687 0.244187 -0.159326 0.807468 0.241581 -0.870859 0.031241 0.823101 0.826291 NaN 0.590927 0.665025 NaN -0.074269 -0.116396 NaN -0.828988 NaN -0.057430 -0.141734 0.807504 -0.434449 -0.435188 0.884510 0.824858 0.331893 0.379398 0.819807 0.392655 0.209601 0.224334 -0.193580 -0.032340 0.006164 0.865894 -0.369892 0.152628 0.159744 -0.197363 -0.856190 0.834468 -0.001831 0.879553 0.650948 0.777415 0.645975 0.932000 0.953123 -0.250997
totalLiabilities 0.411760 0.865611 0.768401 0.709769 0.487973 0.918348 0.923500 0.742267 0.392883 0.900662 0.662771 0.725971 0.628692 0.859897 0.625373 0.370139 0.899257 0.848029 1.000000 0.954615 0.878862 0.505622 0.872681 0.641439 0.970120 0.435577 0.947695 0.856410 0.947142 0.866899 0.694101 0.853062 0.269794 0.996125 0.085466 0.683938 0.738537 0.802678 0.877476 0.890077 0.856988 0.877380 0.543677 0.509598 0.531037 0.903982 -0.925727 0.728288 0.925184 0.844775 -0.305357 0.698409 0.686795 0.872965 0.785365 0.925483 0.856484 0.859523 0.884237 0.874205 0.860719 0.833337 0.729433 -0.855605 0.269385 0.612560 0.758735 0.351790 0.342019 -0.210994 0.856563 0.016026 -0.839369 0.027800 0.819616 0.826542 NaN 0.842960 0.873686 NaN -0.189476 0.283679 NaN -0.836574 NaN 0.043713 -0.032747 0.860719 -0.637636 -0.638754 0.805463 0.770852 0.409057 0.657587 0.875104 0.345203 0.246678 0.266849 -0.170712 -0.073695 -0.151030 0.611044 -0.560490 0.248751 0.255052 0.033360 -0.821129 0.921502 0.055905 0.879211 0.785805 0.946521 0.799458 0.937687 0.922900 -0.389036
totalCurrentLiabilities 0.418024 0.854887 0.736028 0.679849 0.434539 0.888025 0.939323 0.764128 0.430203 0.916535 0.683788 0.705727 0.658702 0.799732 0.585881 0.317074 0.937981 0.865888 0.954615 1.000000 0.867926 0.586169 0.801481 0.594379 0.884354 0.486161 0.840602 0.825653 0.826840 0.765673 0.730521 0.816708 0.311082 0.984086 0.141747 0.691724 0.714295 0.832793 0.891062 0.894074 0.855263 0.916428 0.552596 0.522664 0.542149 0.848551 -0.845348 0.680173 0.846309 0.858159 -0.272698 0.682862 0.699115 0.911313 0.768826 0.845085 0.908512 0.909638 0.918204 0.908872 0.910183 0.860771 0.704485 -0.642009 0.183135 0.670939 0.734643 0.378157 0.400518 -0.194264 0.908552 -0.008655 -0.855664 0.158226 0.820145 0.827028 NaN 0.820569 0.839106 NaN -0.128978 0.139120 NaN -0.834798 NaN 0.014464 -0.199537 0.910183 -0.622526 -0.623381 0.757378 0.778155 0.424892 0.589013 0.911802 0.390790 0.276776 0.272135 -0.160734 -0.071767 -0.116025 0.632265 -0.482464 0.242990 0.254416 -0.066615 -0.874885 0.936298 0.028605 0.862322 0.747549 0.841053 0.700939 0.942459 0.937900 -0.382282
currentAccountsPayable 0.247724 0.657000 0.455766 0.651693 0.087635 0.883558 0.786462 0.738434 0.148692 0.721104 0.121889 0.375132 0.070548 0.837448 0.832400 -0.046564 0.765734 0.871428 0.878862 0.867926 1.000000 0.199358 0.917708 0.691588 0.837532 0.078458 0.863017 0.856835 0.858777 0.876205 0.685014 0.960534 0.035650 0.757249 -0.031463 0.375126 0.615596 0.647255 0.842507 0.927403 0.917517 0.813324 0.251932 0.285045 0.255495 0.853212 -0.772104 0.706385 0.770999 0.848945 -0.399268 0.478917 0.678758 0.804027 0.768045 0.771981 0.782739 0.783113 0.810203 0.803469 0.782541 0.740629 0.590673 -0.700837 0.123243 0.576821 0.472820 0.105503 0.321832 -0.228477 0.782798 0.105888 -0.790943 0.133290 0.826266 0.831019 NaN 0.562194 0.708887 NaN -0.263109 0.189674 NaN -0.832069 NaN 0.051540 -0.077922 0.782541 -0.556924 -0.557819 0.838749 0.795713 0.362631 0.672055 0.816401 0.139483 0.078189 0.104678 -0.325753 -0.062131 -0.181838 0.670760 -0.380782 0.169853 0.175168 -0.327624 -0.935294 0.777745 -0.171141 0.996201 0.889902 0.870833 0.705018 0.858420 0.867654 -0.347260
deferredRevenue 0.224468 0.486229 0.543094 0.178323 0.514986 0.397805 0.471238 0.298200 0.261577 0.483502 0.846771 0.820242 0.817877 0.161264 -0.150455 0.521023 0.623739 0.326641 0.505622 0.586169 0.199358 1.000000 0.150753 0.153231 0.498226 0.968860 0.356319 0.316793 0.349839 0.200506 0.017275 0.193490 0.220291 0.568948 -0.004830 0.683330 0.377101 0.410204 0.258976 0.226284 0.124232 0.419054 0.372125 0.240430 0.336799 0.353955 -0.564241 0.185487 0.566220 0.292374 -0.080879 0.439174 0.060546 0.409829 0.287101 0.564096 0.423886 0.422189 0.420516 0.387773 0.425624 0.374862 0.325836 -0.661638 0.193819 0.316058 0.502630 0.285423 0.189434 -0.327158 0.423975 -0.088445 -0.306402 -0.018531 0.115638 0.126869 NaN 0.645125 0.744915 NaN 0.098968 0.189913 NaN -0.157259 NaN -0.054481 -0.102250 0.425624 -0.352007 -0.352942 0.220806 0.252091 0.238548 0.282386 0.384840 0.497480 0.176858 0.049887 -0.105347 -0.029875 0.213312 0.214213 -0.301597 0.275210 0.290952 0.110560 -0.204592 0.464672 0.383176 0.186012 0.251787 0.344706 0.317440 0.423622 0.409308 -0.268106
currentDebt 0.254958 0.576849 0.393563 0.485957 0.014023 0.859214 0.700523 0.606431 -0.094996 0.605868 0.084080 0.375285 0.023222 0.829806 0.775938 -0.074176 0.666521 0.763865 0.872681 0.801481 0.917708 0.150753 1.000000 0.819215 0.861196 0.036797 0.902176 0.807101 0.896209 0.898908 0.533511 0.906621 -0.216066 NaN -0.254903 0.320809 0.566713 0.473624 0.704064 0.803219 0.795962 0.655361 0.031319 0.057852 0.034857 0.813615 -0.808128 0.595203 0.808094 0.690086 -0.360848 0.347169 0.516110 0.645192 0.621346 0.808128 0.612384 0.616952 0.658070 0.646424 0.620607 0.573425 0.530510 0.325267 0.257982 0.438622 0.378549 -0.122699 0.201296 -0.304550 0.612428 0.208823 -0.642247 0.208424 0.688923 0.688923 NaN 0.580263 0.731666 NaN -0.357346 0.191521 NaN -0.711391 NaN 0.058855 -0.088470 0.620607 -0.531687 -0.533098 0.857352 0.745244 0.379153 0.684401 0.655862 -0.010858 -0.162700 -0.147204 -0.531586 -0.119853 -0.090191 0.653090 -0.439440 0.051480 0.088194 -0.437929 -0.781290 0.695024 0.026306 0.913803 0.905103 0.920729 0.835740 0.762726 0.760828 -0.623193
shortTermDebt 0.076011 0.457609 0.289314 0.316223 0.081903 0.608295 0.470018 0.512873 0.021192 0.420214 0.049714 0.271044 0.003103 0.588378 0.616287 0.043708 0.524235 0.478979 0.641439 0.594379 0.691588 0.153231 0.819215 1.000000 0.682531 0.096324 0.669819 0.552354 0.692836 0.713319 0.315259 0.685390 -0.016852 -0.894331 -0.095759 0.230481 0.377113 0.378630 0.508775 0.554096 0.558119 0.487853 0.130499 0.130099 0.130404 0.585826 -0.548516 0.449509 0.549006 0.483046 -0.493270 0.298977 0.321940 0.476413 0.493315 0.548277 0.443045 0.445907 0.483969 0.464941 0.454468 0.472342 0.375241 0.519870 0.401979 0.318126 0.298038 0.077917 0.196877 -0.337312 0.443119 -0.153525 -0.388243 0.397812 0.467383 0.475717 NaN 0.407778 0.565665 NaN -0.291815 0.269672 NaN -0.501132 NaN -0.011715 -0.022186 0.454468 -0.465052 -0.465627 0.537911 0.514644 0.274406 0.585495 0.479234 0.020068 0.018291 0.051807 -0.230898 -0.064350 -0.224131 0.312626 -0.347100 0.158800 0.156056 -0.264161 -0.586783 0.443527 -0.136371 0.666027 0.713645 0.719021 0.639251 0.538351 0.528133 -0.289076
totalNonCurrentLiabilities 0.343934 0.806133 0.710284 0.660629 0.460054 0.866536 0.825667 0.723037 0.292263 0.806963 0.573832 0.697052 0.528978 0.827764 0.642490 0.352660 0.836408 0.756125 0.970120 0.884354 0.837532 0.498226 0.861196 0.682531 1.000000 0.463957 0.968745 0.807993 0.974382 0.901867 0.557459 0.845340 0.197449 0.988982 0.018682 0.611599 0.686521 0.700409 0.784798 0.815132 0.780705 0.787278 0.449831 0.403302 0.432467 0.907123 -0.921828 0.712632 0.920965 0.767181 -0.406204 0.662498 0.604145 0.781026 0.724611 0.921621 0.759291 0.763845 0.795264 0.779975 0.765056 0.743053 0.673252 -0.779554 0.307183 0.487398 0.713024 0.283936 0.237712 -0.284803 0.759405 -0.028542 -0.726384 -0.045030 0.711516 0.723077 NaN 0.824367 0.887726 NaN -0.220191 0.474686 NaN -0.742580 NaN 0.060488 0.005710 0.765056 -0.610952 -0.612102 0.763780 0.699248 0.374542 0.719022 0.783742 0.304657 0.193856 0.201764 -0.200715 -0.069459 -0.141084 0.530848 -0.552395 0.241709 0.244298 0.028602 -0.734907 0.822281 0.068391 0.837477 0.801877 0.970286 0.816617 0.857163 0.834946 -0.375828
capitalLeaseObligations 0.252524 0.494971 0.531461 0.161526 0.549540 0.273158 0.406351 0.441260 0.319272 0.417652 0.917006 0.920702 0.901343 0.075130 -0.269203 0.570435 0.616279 0.161628 0.435577 0.486161 0.078458 0.968860 0.036797 0.096324 0.463957 1.000000 0.289698 0.190485 0.277557 0.126089 -0.074733 0.065317 0.326678 0.668254 0.155156 0.654196 0.207082 0.346688 0.175498 0.140987 0.025974 0.353982 0.356897 0.210357 0.315597 0.501002 -0.535860 0.240817 0.535828 0.206232 -0.116643 0.481096 0.014218 0.349772 0.305345 0.535723 0.347124 0.335915 0.360231 0.328039 0.347075 0.330695 0.276586 0.298273 0.288622 0.302752 0.543069 0.363742 0.269059 -0.334217 0.347124 -0.272209 -0.212983 -0.260824 -0.050628 -0.026458 NaN 0.586456 0.713037 NaN 0.006856 0.249855 NaN -0.025578 NaN 0.042389 -0.137647 0.347075 -0.362573 -0.363665 0.026291 0.107066 0.209901 0.517509 0.322194 0.536428 0.201071 0.058282 -0.025978 -0.032807 0.114809 0.007390 -0.264261 0.206264 0.202800 0.226216 -0.079933 0.380217 0.456455 0.055834 0.260368 0.280154 0.223002 0.314407 0.284794 -0.219074
longTermDebt 0.333751 0.704016 0.602595 0.646034 0.318276 0.872023 0.767273 0.606464 0.160165 0.755827 0.472153 0.614997 0.428524 0.837633 0.641051 0.202699 0.747145 0.784005 0.947695 0.840602 0.863017 0.356319 0.902176 0.669819 0.968745 0.289698 1.000000 0.859198 0.995181 0.948164 0.543572 0.878625 0.024442 0.999185 -0.111696 0.481163 0.660764 0.603522 0.732815 0.799763 0.773234 0.715336 0.312644 0.295383 0.302408 0.906985 -0.942895 0.706337 0.942897 0.763752 -0.267432 0.584366 0.562212 0.706607 0.634205 0.942850 0.690990 0.696240 0.722504 0.704481 0.696092 0.651812 0.671915 0.023430 0.225335 0.463162 0.619255 0.139461 0.189826 -0.333325 0.691104 0.153821 -0.741573 -0.101707 0.740343 0.745659 NaN 0.725615 0.827615 NaN -0.254755 0.152167 NaN -0.758170 NaN 0.066163 0.000845 0.696092 -0.563486 -0.564703 0.814164 0.705121 0.348500 0.637939 0.713992 0.299716 0.167023 0.141442 -0.304373 -0.067504 -0.131853 0.578459 -0.468194 0.194497 0.198497 -0.095171 -0.725145 0.766439 0.031550 0.864238 0.855128 0.997660 0.804836 0.830095 0.813330 -0.346285
currentLongTermDebt 0.484995 0.618235 0.521710 0.693227 0.152698 0.823044 0.758398 0.483231 0.157088 0.734723 0.487381 0.512395 0.469784 0.757333 0.508503 0.008978 0.710454 0.868864 0.856410 0.825653 0.856835 0.316793 0.807101 0.552354 0.807993 0.190485 0.859198 1.000000 0.820612 0.810290 0.535367 0.840534 -0.085211 NaN -0.188637 0.418017 0.589534 0.616931 0.726128 0.793739 0.756265 0.727843 0.250314 0.357456 0.295445 0.811449 -0.862553 0.586528 0.862553 0.790384 -0.089740 0.573790 0.485072 0.715689 0.640282 0.862553 0.704266 0.703859 0.727464 0.713507 0.702279 0.625297 0.631983 0.339075 -0.023458 0.534462 0.562269 0.102963 0.232121 -0.274251 0.704162 0.324785 -0.786424 -0.085930 0.715211 0.722316 NaN 0.523946 0.708808 NaN -0.143629 -0.580449 NaN -0.734202 NaN -0.007952 0.057048 0.702279 -0.507449 -0.507938 0.835759 0.759360 0.314432 0.467530 0.715742 0.385391 0.134409 0.146174 -0.418151 -0.103423 -0.005035 0.766027 -0.358682 0.143278 0.155138 -0.272694 -0.755443 0.761262 0.083272 0.859936 0.766274 0.850847 0.724722 0.833484 0.834663 -0.276069
longTermDebtNoncurrent 0.250159 0.667144 0.548739 0.573618 0.241328 0.866526 0.734582 0.601917 0.041130 0.706566 0.468597 0.660275 0.414320 0.798491 0.658034 0.130869 0.725704 0.770241 0.947142 0.826840 0.858777 0.349839 0.896209 0.692836 0.974382 0.277557 0.995181 0.820612 1.000000 0.930426 0.478693 0.863792 -0.073325 0.999185 -0.196186 0.431064 0.641254 0.545360 0.699670 0.784413 0.750194 0.693511 0.189817 0.181097 0.182858 0.877167 -0.939457 0.633796 0.939459 0.719047 -0.342258 0.449188 0.509049 0.682486 0.631328 0.939384 0.658515 0.665853 0.700146 0.676992 0.665106 0.609833 0.649004 -1.000000 0.214756 0.470184 0.552649 0.031209 0.204932 -0.370495 0.658663 0.127269 -0.671219 -0.091539 0.666579 0.666579 NaN 0.723330 0.829487 NaN -0.439226 0.169437 NaN -0.685251 NaN 0.061500 0.044360 0.665106 -0.577494 -0.579271 0.803033 0.729932 0.449874 0.643803 0.688751 0.242296 0.044722 0.010094 -0.353399 -0.075511 -0.031525 0.573900 -0.385252 0.329490 0.329195 -0.192152 -0.710001 0.727467 -0.089020 0.854811 0.862000 0.994241 0.804964 0.805407 0.789419 -0.572613
shortLongTermDebtTotal 0.205381 0.630319 0.476080 0.618416 0.172461 0.797990 0.687921 0.645111 0.085178 0.673207 0.215592 0.410752 0.169580 0.857749 0.793115 0.058345 0.695274 0.707604 0.866899 0.765673 0.876205 0.200506 0.898908 0.713319 0.901867 0.126089 0.948164 0.810290 0.930426 1.000000 0.527802 0.913337 -0.005108 0.999185 -0.073444 0.336796 0.581361 0.517819 0.711479 0.801185 0.798084 0.661122 0.196046 0.189754 0.183687 0.875799 -0.826470 0.698126 0.826485 0.728663 -0.323639 0.475523 0.572454 0.654284 0.594091 0.826442 0.640475 0.636843 0.668513 0.656475 0.643516 0.591728 0.613607 0.169170 0.186671 0.469459 0.516325 0.062440 0.249967 -0.279678 0.640555 0.094727 -0.667967 0.021846 0.711982 0.720177 NaN 0.556024 0.710379 NaN -0.279188 0.364807 NaN -0.728798 NaN 0.016112 -0.005894 0.643516 -0.527109 -0.528274 0.772784 0.662827 0.308983 0.642161 0.666324 0.075743 0.019467 0.038049 -0.336280 -0.058074 -0.173970 0.499965 -0.376168 0.165444 0.169494 -0.197757 -0.751446 0.680187 -0.111189 0.869421 0.865472 0.950603 0.738646 0.740757 0.724515 -0.335041
otherCurrentLiabilities 0.487111 0.765688 0.666028 0.705539 0.402439 0.651409 0.842151 0.656226 0.623051 0.840277 0.213786 0.063507 0.244081 0.752774 0.487486 0.260617 0.674423 0.720334 0.694101 0.730521 0.685014 0.017275 0.533511 0.315259 0.557459 -0.074733 0.543572 0.535367 0.478693 0.527802 1.000000 0.594541 0.502524 0.732979 0.437295 0.495081 0.583270 0.834202 0.906354 0.849155 0.876690 0.826447 0.662859 0.699620 0.669841 0.783545 -0.448447 0.612131 0.454745 0.803561 -0.021481 0.603665 0.876594 0.837545 0.687013 0.448092 0.841841 0.844755 0.832963 0.859632 0.840977 0.820483 0.638538 -0.607536 -0.002108 0.628293 0.673142 0.499934 0.402263 0.247977 0.841773 -0.008278 -0.842087 0.140585 0.864609 0.869281 NaN 0.459543 0.332062 NaN -0.234436 -0.027566 NaN -0.882834 NaN 0.026777 -0.530352 0.840977 -0.465398 -0.465367 0.586692 0.673980 0.379095 0.193904 0.852597 0.235667 0.399038 0.503559 0.122798 -0.077827 -0.262965 0.522671 -0.352298 0.182498 0.201991 0.140507 -0.804841 0.835601 -0.192688 0.678382 0.423885 0.537318 0.443250 0.809162 0.806896 -0.303994
otherNonCurrentLiabilities 0.189234 0.615727 0.436170 0.659466 0.087656 0.859095 0.723974 0.694574 0.080050 0.679763 0.103079 0.347008 0.054512 0.853911 0.832871 -0.049543 0.720178 0.816822 0.853062 0.816708 0.960534 0.193490 0.906621 0.685390 0.845340 0.065317 0.878625 0.840534 0.863792 0.913337 0.594541 1.000000 -0.006588 -0.998908 -0.085241 0.343888 0.628310 0.577911 0.778306 0.872055 0.862672 0.741305 0.211617 0.215281 0.203168 0.854563 -0.755667 0.698722 0.757783 0.781659 -0.381849 0.415273 0.633264 0.730776 0.680074 0.755505 0.715401 0.717263 0.739684 0.730310 0.715358 0.674800 0.574546 -0.592206 0.147011 0.459810 0.445377 0.055102 0.187064 -0.256195 0.715479 0.139655 -0.742137 0.072260 0.773980 0.781168 NaN 0.542988 0.730754 NaN -0.254825 0.326336 NaN -0.789883 NaN 0.061420 0.010323 0.715358 -0.517101 -0.518239 0.800094 0.757395 0.365813 0.725983 0.745910 0.123797 0.056630 0.067595 -0.325563 -0.063927 -0.186036 0.606311 -0.399893 0.187868 0.192292 -0.297532 -0.861928 0.720536 -0.153389 0.964779 0.883190 0.885533 0.727395 0.800781 0.805411 -0.355454
totalShareholderEquity 0.313628 0.715564 0.715612 0.511622 0.721719 0.089931 0.502743 0.512736 0.885293 0.541225 0.522858 0.333950 0.548435 0.345060 -0.009579 0.656336 0.457273 0.034121 0.269794 0.311082 0.035650 0.220291 -0.216066 -0.016852 0.197449 0.326678 0.024442 -0.085211 -0.073325 -0.005108 0.502524 -0.006588 1.000000 -0.989137 0.932806 0.465231 0.070404 0.665453 0.504547 0.313166 0.330081 0.492031 0.828847 0.752453 0.800232 0.559791 -0.056643 0.405075 0.071652 0.306602 0.007540 0.720247 0.434434 0.518128 0.421966 0.055745 0.520539 0.522014 0.510388 0.538439 0.520946 0.604852 0.303349 -0.719575 0.020539 0.339415 0.705619 0.895728 0.392579 0.470080 0.520332 -0.503967 -0.312153 0.073129 0.198481 0.243511 NaN 0.083056 0.090606 NaN -0.213350 0.234744 NaN -0.328813 NaN 0.086618 -0.157070 0.520946 -0.353033 -0.352521 -0.200473 0.177509 0.432549 0.056191 0.496826 0.371561 0.674720 0.733727 0.656947 -0.120690 -0.414813 -0.260289 -0.299290 0.339590 0.353990 0.696560 -0.195497 0.447152 -0.259242 -0.016492 -0.067294 0.021437 0.096888 0.318187 0.273339 -0.354171
treasuryStock 0.847258 0.996896 -0.999161 -0.807003 -0.183357 0.999338 0.874078 0.700234 0.731262 0.838693 -0.878816 -0.880362 0.880779 0.682233 NaN 0.418525 0.940556 -0.611789 0.996125 0.984086 0.757249 0.568948 NaN -0.894331 0.988982 0.668254 0.999185 NaN 0.999185 0.999185 0.732979 -0.998908 -0.989137 1.000000 -0.882359 -0.531182 0.531409 0.741946 0.999831 0.609745 -0.055358 -0.999191 0.993306 0.945035 0.947761 0.726943 -0.987829 0.726943 0.987829 0.997996 -0.999350 NaN 0.725820 -0.997647 0.999881 -0.999728 -0.997707 -0.994021 -0.997575 -0.999760 -0.997707 -0.841941 0.978822 NaN -0.678506 -0.972253 0.928897 0.794086 -0.992819 NaN -0.997707 -0.266299 -0.845817 NaN 0.673567 0.673567 NaN NaN NaN NaN NaN NaN NaN -0.682276 NaN NaN NaN -0.997707 -0.999991 -0.999991 0.985567 -0.999718 -0.998156 NaN -0.994126 -0.986644 -0.997707 0.999831 -0.989137 0.999587 -0.990638 -0.932956 -0.976494 -0.998504 -0.997865 -0.996811 -0.998670 0.936484 0.832725 0.792631 0.744392 0.999116 -0.860222 0.800476 -0.858983 0.861291
retainedEarnings 0.203581 0.547825 0.491602 0.411573 0.499352 -0.080783 0.318588 0.498072 0.767830 0.350804 0.269849 0.115188 0.293560 0.257475 0.090037 0.441852 0.300467 -0.116401 0.085466 0.141747 -0.031463 -0.004830 -0.254903 -0.095759 0.018682 0.155156 -0.111696 -0.188637 -0.196186 -0.073444 0.437295 -0.085241 0.932806 -0.882359 1.000000 0.196337 -0.170450 0.476067 0.388850 0.246462 0.283143 0.340819 0.611088 0.565608 0.583968 0.485881 0.122010 0.372655 -0.114082 0.207886 0.002538 0.618557 0.393310 0.370377 0.315418 -0.122750 0.371824 0.368884 0.359634 0.398771 0.369245 0.458515 0.152015 -0.610877 -0.165822 0.241226 0.506801 0.785624 0.359134 0.507240 0.371560 -0.511164 -0.160165 0.073050 0.109486 0.143532 NaN -0.156287 -0.126570 NaN -0.237943 0.291619 NaN -0.210506 NaN 0.102622 -0.156675 0.369245 -0.239231 -0.238255 -0.338802 0.008160 0.299549 -0.002847 0.355522 0.169553 0.526261 0.607443 0.594914 -0.094276 -0.408901 -0.382016 -0.115904 0.224370 0.240197 0.561369 -0.140647 0.264632 -0.382419 -0.074794 -0.094542 -0.113558 -0.077352 0.138845 0.097075 -0.265766
commonStock 0.205741 0.736581 0.837034 0.370650 0.788570 0.648290 0.759485 0.446489 0.457535 0.742709 0.713638 0.715868 0.699446 0.528125 -0.023911 0.769187 0.688021 0.488127 0.683938 0.691724 0.375126 0.683330 0.320809 0.230481 0.611599 0.654196 0.481163 0.418017 0.431064 0.336796 0.495081 0.343888 0.465231 -0.531182 0.196337 1.000000 0.674860 0.697992 0.599047 0.507215 0.463315 0.629166 0.744634 0.541946 0.668312 0.502146 -0.599859 0.478336 0.604904 0.452702 -0.018087 0.449759 0.446477 0.633672 0.539129 0.599381 0.625317 0.632402 0.640841 0.642227 0.631852 0.619587 0.501251 NaN 0.477762 0.475233 0.676563 0.393085 0.302123 -0.098577 0.625241 -0.155074 -0.554350 -0.027625 0.403715 0.431299 NaN 0.566079 0.697527 NaN 0.037340 0.083800 NaN -0.477964 NaN -0.034623 -0.072172 0.631852 -0.574724 -0.576741 0.429348 0.515198 0.382330 0.198212 0.621864 0.245007 0.203398 0.212850 -0.081884 -0.091146 -0.212581 0.294142 -0.577561 0.280804 0.286818 0.437230 -0.391310 0.762605 0.329990 0.369626 0.335257 0.468724 0.507963 0.614226 0.602895 -0.371524
commonStockSharesOutstanding 0.299276 0.571772 0.545138 0.432202 0.330252 0.761355 0.720095 0.419483 0.256293 0.728166 0.518725 0.547425 0.516603 0.599503 0.285416 0.241613 0.658377 0.742670 0.738537 0.714295 0.615596 0.377101 0.566713 0.377113 0.686521 0.207082 0.660764 0.589534 0.641254 0.581361 0.583270 0.628310 0.070404 0.531409 -0.170450 0.674860 1.000000 0.666402 0.679235 0.652347 0.624605 0.692336 0.512284 0.464938 0.504249 0.496196 -0.649879 0.410876 0.654064 0.706573 -0.091753 0.408791 0.552448 0.666766 0.531597 0.649661 0.668818 0.669801 0.673654 0.673523 0.672999 0.641498 0.619851 -0.690942 0.344068 0.478114 0.486340 0.153411 0.133000 -0.334553 0.668984 0.089615 -0.723791 0.107880 0.687691 0.698411 NaN 0.567601 0.664886 NaN 0.022519 0.095601 NaN -0.709309 NaN -0.226628 0.080571 0.672999 -0.441788 -0.443257 0.739944 0.717405 0.352495 0.346494 0.691834 0.286653 0.196994 0.216755 -0.171275 -0.024883 -0.065968 0.646548 -0.486392 0.212570 0.211376 -0.018994 -0.653922 0.738259 0.146017 0.619275 0.454686 0.653192 0.639511 0.763457 0.771767 -0.278767
grossProfit 0.542231 0.928666 0.855436 0.776796 0.616823 0.693223 0.936037 0.702571 0.790546 0.948407 0.657278 0.488204 0.676927 0.718074 0.349559 0.473900 0.860425 0.720681 0.802678 0.832793 0.647255 0.410204 0.473624 0.378630 0.700409 0.346688 0.603522 0.616931 0.545360 0.517819 0.834202 0.577911 0.665453 0.741946 0.476067 0.697992 0.666402 1.000000 0.932865 0.807451 0.794263 0.951054 0.872014 0.868873 0.879462 0.750931 -0.582763 0.580455 0.588069 0.834230 -0.101777 0.840610 0.742058 0.954739 0.795284 0.582100 0.954904 0.952463 0.953150 0.957865 0.955881 0.954306 0.711721 -0.611297 0.138736 0.686084 0.868048 0.730529 0.480845 0.081913 0.954876 -0.189928 -0.857212 0.124677 0.833796 0.835221 NaN 0.722861 0.569586 NaN -0.126415 -0.084260 NaN -0.846360 NaN -0.038337 -0.064244 0.955881 -0.616889 -0.616972 0.532739 0.749314 0.555692 0.358063 0.948290 0.557023 0.661444 0.703728 0.312352 -0.113940 -0.294752 0.450879 -0.500928 0.350094 0.363301 0.301917 -0.764139 0.924671 -0.153489 0.632352 0.434222 0.600535 0.578459 0.889749 0.874286 -0.421514
totalRevenue 0.443668 0.899559 0.758806 0.797385 0.449243 0.808844 0.946325 0.818852 0.607391 0.923025 0.443991 0.415075 0.444748 0.862235 0.655928 0.294248 0.872680 0.812807 0.877476 0.891062 0.842507 0.258976 0.704064 0.508775 0.784798 0.175498 0.732815 0.726128 0.699670 0.711479 0.906354 0.778306 0.504547 0.999831 0.388850 0.599047 0.679235 0.932865 1.000000 0.959984 0.959437 0.967715 0.690692 0.695137 0.688783 0.839842 -0.658625 0.711488 0.662409 0.907186 -0.213757 0.741844 0.852312 0.969972 0.846277 0.658136 0.962090 0.961003 0.970290 0.981230 0.962385 0.951021 0.712461 -0.595125 0.107410 0.693361 0.760254 0.535886 0.456779 0.018074 0.962076 -0.109925 -0.898122 0.128990 0.926757 0.926989 NaN 0.615143 0.608607 NaN -0.242549 0.143043 NaN -0.930754 NaN -0.004444 -0.097227 0.962385 -0.640601 -0.641021 0.682253 0.808297 0.506087 0.495792 0.976884 0.335777 0.436713 0.504135 0.061279 -0.104909 -0.316914 0.545734 -0.469781 0.284288 0.297571 0.092397 -0.913576 0.936973 -0.225136 0.837049 0.656436 0.732208 0.640065 0.928152 0.919984 -0.428955
costOfRevenue 0.341991 0.809477 0.639835 0.742429 0.301815 0.850874 0.887715 0.842481 0.400148 0.858110 0.288471 0.412662 0.261701 0.876656 0.779339 0.148863 0.851087 0.842316 0.890077 0.894074 0.927403 0.226284 0.803219 0.554096 0.815132 0.140987 0.799763 0.793739 0.784413 0.801185 0.849155 0.872055 0.313166 0.609745 0.246462 0.507215 0.652347 0.807451 0.959984 1.000000 0.991412 0.914844 0.484645 0.487488 0.474475 0.826630 -0.709183 0.731718 0.710648 0.913795 -0.284765 0.650776 0.842517 0.913382 0.830310 0.708897 0.899156 0.898478 0.916533 0.926507 0.898609 0.877019 0.666050 -0.456865 0.060123 0.647169 0.627567 0.332945 0.389018 -0.080490 0.899166 -0.023366 -0.865241 0.099191 0.895937 0.899763 NaN 0.583937 0.656841 NaN -0.262949 0.229530 NaN -0.903289 NaN 0.026201 -0.126678 0.898609 -0.614661 -0.615365 0.763528 0.798388 0.427528 0.601261 0.928043 0.189452 0.219269 0.280912 -0.169410 -0.083529 -0.258245 0.607673 -0.404713 0.215348 0.225861 -0.086428 -0.948543 0.879867 -0.218439 0.924771 0.785162 0.798280 0.659097 0.900952 0.899318 -0.400964
costofGoodsAndServicesSold 0.329702 0.794146 0.614049 0.743747 0.276703 0.821039 0.867449 0.833651 0.409731 0.835080 0.168144 0.273903 0.150387 0.893207 0.804846 0.125087 0.804385 0.812831 0.856988 0.855263 0.917517 0.124232 0.795962 0.558119 0.780705 0.025974 0.773234 0.756265 0.750194 0.798084 0.876690 0.862672 0.330081 -0.055358 0.283143 0.463315 0.624605 0.794263 0.959437 0.991412 1.000000 0.893155 0.482511 0.495104 0.473931 0.825970 -0.658109 0.748364 0.660117 0.896557 -0.273602 0.617588 0.858986 0.893997 0.807370 0.657806 0.880988 0.880892 0.896009 0.910462 0.880752 0.860125 0.652804 -0.456865 0.059068 0.636922 0.609460 0.336419 0.396441 -0.029071 0.880983 -0.032028 -0.850322 0.110629 0.902273 0.905849 NaN 0.505993 0.584541 NaN -0.275417 0.253647 NaN -0.910291 NaN 0.022839 -0.124924 0.880752 -0.595187 -0.595789 0.737444 0.781501 0.421232 0.560437 0.910530 0.140026 0.223642 0.301914 -0.139616 -0.085608 -0.297261 0.573125 -0.397018 0.207061 0.218954 -0.079744 -0.945293 0.857667 -0.259080 0.913797 0.762030 0.773908 0.634411 0.874628 0.872669 -0.393780
operatingIncome 0.458929 0.893051 0.756111 0.763553 0.448635 0.798757 0.945606 0.800703 0.607300 0.924569 0.603438 0.542615 0.602194 0.772811 0.567768 0.297820 0.916894 0.823113 0.877380 0.916428 0.813324 0.419054 0.655361 0.487853 0.787278 0.353982 0.715336 0.727843 0.693511 0.661122 0.826447 0.741305 0.492031 -0.999191 0.340819 0.629166 0.692336 0.951054 0.967715 0.914844 0.893155 1.000000 0.690820 0.690299 0.690525 0.788734 -0.674718 0.627401 0.678289 0.893131 -0.218218 0.758644 0.779647 0.997891 0.866092 0.674196 0.990890 0.987522 0.997785 0.994444 0.991123 0.957146 0.696995 -0.502860 0.103969 0.739055 0.766576 0.546616 0.503631 -0.071082 0.990898 -0.139099 -0.888495 0.157444 0.875981 0.877988 NaN 0.693512 0.673841 NaN -0.161139 0.028870 NaN -0.884746 NaN -0.039476 -0.013874 0.991123 -0.620729 -0.621065 0.661884 0.827924 0.547484 0.512870 0.997020 0.483794 0.513949 0.520334 0.089999 -0.098661 -0.242676 0.568972 -0.421188 0.325019 0.334519 0.059216 -0.896415 0.930706 -0.198902 0.801964 0.623892 0.714454 0.639096 0.938327 0.934020 -0.438958
sellingGeneralAndAdministrative 0.471890 0.824803 0.875038 0.603288 0.812920 0.409702 0.744555 0.456471 0.882441 0.786074 0.644537 0.418213 0.676903 0.512570 -0.077019 0.728327 0.628351 0.377750 0.543677 0.552596 0.251932 0.372125 0.031319 0.130499 0.449831 0.356897 0.312644 0.250314 0.189817 0.196046 0.662859 0.211617 0.828847 0.993306 0.611088 0.744634 0.512284 0.872014 0.690692 0.484645 0.482511 0.690820 1.000000 0.920636 0.979061 0.564602 -0.347087 0.437352 0.358715 0.556643 0.077075 0.782217 0.543980 0.703789 0.548668 0.346280 0.710245 0.710389 0.701108 0.716732 0.713211 0.760205 0.552068 -0.683127 0.237721 0.476565 0.844762 0.843705 0.372621 0.300209 0.710155 -0.284880 -0.614049 -0.040461 0.515418 0.539612 NaN 0.553937 0.353801 NaN -0.044561 -0.209663 NaN -0.591620 NaN -0.005802 -0.097404 0.713211 -0.541199 -0.541251 0.205047 0.476250 0.490332 0.072567 0.689425 0.498964 0.710256 0.784664 0.532506 -0.126953 -0.365597 0.118616 -0.537080 0.348906 0.363626 0.653448 -0.390186 0.723647 -0.029449 0.220387 0.078174 0.305713 0.380514 0.610982 0.580017 -0.362920
researchAndDevelopment 0.660126 0.761047 0.770091 0.686437 0.647293 0.360294 0.716183 0.383482 0.939075 0.859643 0.574098 0.234415 0.625391 0.450217 -0.060027 0.521932 0.578930 0.468613 0.509598 0.522664 0.285045 0.240430 0.057852 0.130099 0.403302 0.210357 0.295383 0.357456 0.181097 0.189754 0.699620 0.215281 0.752453 0.945035 0.565608 0.541946 0.464938 0.868873 0.695137 0.487488 0.495104 0.690299 0.920636 1.000000 0.975141 0.503916 -0.307569 0.383129 0.320575 0.660501 0.098313 0.803981 0.548278 0.698986 0.506979 0.306952 0.716205 0.715628 0.694455 0.709629 0.717007 0.751663 0.622794 -0.669572 0.037778 0.475120 0.840910 0.879275 0.342681 0.318910 0.716130 -0.155459 -0.668546 -0.019749 0.587835 0.606325 NaN 0.583294 0.227358 NaN -0.014333 -0.262385 NaN -0.651797 NaN -0.029641 -0.134793 0.717007 -0.417709 -0.416805 0.252711 0.477465 0.416216 0.010598 0.689485 0.623821 0.804282 0.898362 0.642386 -0.097318 -0.239072 0.250069 -0.457127 0.277981 0.295056 0.533230 -0.443514 0.696195 -0.091465 0.258965 0.028533 0.290032 0.329519 0.665737 0.638740 -0.244700
operatingExpenses 0.572448 0.801023 0.838546 0.642792 0.752450 0.385603 0.735394 0.412149 0.923446 0.824611 0.639579 0.361470 0.680616 0.474370 -0.096293 0.649677 0.612571 0.419000 0.531037 0.542149 0.255495 0.336799 0.034857 0.130404 0.432467 0.315597 0.302408 0.295445 0.182858 0.183687 0.669841 0.203168 0.800232 0.947761 0.583968 0.668312 0.504249 0.879462 0.688783 0.474475 0.473931 0.690525 0.979061 0.975141 1.000000 0.525778 -0.335134 0.407879 0.347419 0.606406 0.085533 0.805753 0.534342 0.700752 0.526608 0.334405 0.712519 0.712320 0.697471 0.711469 0.714629 0.761574 0.599221 -0.658796 0.161806 0.468473 0.855209 0.873310 0.352826 0.288079 0.712448 -0.227447 -0.639083 -0.016760 0.543788 0.565755 NaN 0.592048 0.307661 NaN -0.022206 -0.248921 NaN -0.615511 NaN -0.028591 -0.117314 0.714629 -0.485221 -0.484821 0.223765 0.473560 0.457266 0.042223 0.687971 0.583538 0.770798 0.853122 0.599335 -0.112572 -0.298877 0.178370 -0.514154 0.321182 0.336563 0.611690 -0.405425 0.714853 -0.040983 0.225189 0.043099 0.296389 0.361877 0.642289 0.612069 -0.307161
investmentIncomeNet 0.274194 0.888126 0.755203 0.778847 0.491234 0.798712 0.856471 0.780964 0.530162 0.829459 0.430740 0.508470 0.403495 0.911404 0.726179 0.362552 0.798460 0.696372 0.903982 0.848551 0.853212 0.353955 0.813615 0.585826 0.907123 0.501002 0.906985 0.811449 0.877167 0.875799 0.783545 0.854563 0.559791 0.726943 0.485881 0.502146 0.496196 0.750931 0.839842 0.826630 0.825970 0.788734 0.564602 0.503916 0.525778 1.000000 -0.850267 0.926565 0.850250 0.837651 -0.339038 0.755733 0.767215 0.797428 0.762469 0.850035 0.778251 0.789868 0.805749 0.810664 0.778372 0.767520 0.668657 -0.558881 0.088087 0.468128 0.789272 0.480997 0.305605 -0.144594 0.778251 0.003917 -0.763552 -0.157478 0.763662 0.774766 NaN 0.596289 0.790202 NaN -0.244344 0.365355 NaN -0.789582 NaN 0.214200 -0.184138 0.778372 -0.605020 -0.605868 0.608994 0.602654 0.408269 0.719348 0.800227 0.250136 0.311755 0.333327 -0.093260 -0.102570 -0.315976 0.320135 -0.522840 0.263829 0.274255 0.139623 -0.743091 0.850233 -0.088586 0.855031 0.868891 0.907590 0.692416 0.821380 0.795514 -0.423555
netInterestIncome -0.330298 -0.685633 -0.650651 -0.558858 -0.435231 -0.856790 -0.775613 -0.495074 -0.192781 -0.762602 -0.708969 -0.779820 -0.666459 -0.736710 -0.421410 -0.363298 -0.748334 -0.822858 -0.925727 -0.845348 -0.772104 -0.564241 -0.808128 -0.548516 -0.921828 -0.535860 -0.942895 -0.862553 -0.939457 -0.826470 -0.448447 -0.755667 -0.056643 -0.987829 0.122010 -0.599859 -0.649879 -0.582763 -0.658625 -0.709183 -0.658109 -0.674718 -0.347087 -0.307569 -0.335134 -0.850267 1.000000 -0.651487 -0.999999 -0.716228 0.166028 -0.600324 -0.471712 -0.663584 -0.565214 -0.999989 -0.653394 -0.657647 -0.683812 -0.660868 -0.659103 -0.593894 -0.718302 -0.862045 -0.241398 -0.427856 -0.640493 -0.169456 -0.192718 0.327336 -0.653480 -0.218319 0.735176 0.319659 -0.644364 -0.654743 NaN -0.789514 -0.861557 NaN 0.149813 -0.187113 NaN 0.663107 NaN -0.121390 0.024330 -0.659103 0.496637 0.498190 -0.791933 -0.644609 -0.284034 -0.542459 -0.667037 -0.288286 -0.086300 -0.066532 0.289186 0.038228 0.012973 -0.609468 0.475974 -0.184571 -0.186392 -0.035069 0.624605 -0.784109 -0.213662 -0.778916 -0.731506 -0.934729 -0.760823 -0.835489 -0.828531 0.302082
interestIncome 0.153526 0.743119 0.615986 0.681448 0.406172 0.666563 0.709159 0.786807 0.381565 0.683462 0.281853 0.297026 0.283949 0.850893 0.759452 0.320887 0.591943 0.517258 0.728288 0.680173 0.706385 0.185487 0.595203 0.449509 0.712632 0.240817 0.706337 0.586528 0.633796 0.698126 0.612131 0.698722 0.405075 0.726943 0.372655 0.478336 0.410876 0.580455 0.711488 0.731718 0.748364 0.627401 0.437352 0.383129 0.407879 0.926565 -0.651487 1.000000 0.651403 0.689349 -0.192122 0.568280 0.574297 0.637227 0.623797 0.651156 0.619782 0.646232 0.644998 0.660139 0.618307 0.637730 0.516206 -0.692064 0.137310 0.405964 0.660250 0.351687 0.257031 -0.019626 0.619855 0.035962 -0.624210 -0.279784 0.615154 0.634606 NaN 0.345755 0.538582 NaN -0.061155 0.501661 NaN -0.654418 NaN 0.309732 0.025082 0.618307 -0.575362 -0.576856 0.391860 0.452885 0.368501 0.676650 0.638370 0.046891 0.162015 0.213466 -0.081959 0.160180 -0.383165 0.158780 -0.509904 0.235837 0.247161 0.150852 -0.635952 0.706620 -0.140609 0.705996 0.749039 0.701062 0.578690 0.664068 0.634509 -0.408488
interestExpense 0.341442 0.688226 0.654350 0.561989 0.443611 0.856806 0.776799 0.500507 0.207193 0.765165 0.707107 0.777611 0.665924 0.738718 0.427964 0.372944 0.750334 0.824518 0.925184 0.846309 0.770999 0.566220 0.808094 0.549006 0.920965 0.535828 0.942897 0.862553 0.939459 0.826485 0.454745 0.757783 0.071652 0.987829 -0.114082 0.604904 0.654064 0.588069 0.662409 0.710648 0.660117 0.678289 0.358715 0.320575 0.347419 0.850250 -0.999999 0.651403 1.000000 0.716323 -0.180757 0.600524 0.477551 0.667355 0.569916 0.999988 0.657305 0.661487 0.687256 0.664703 0.662925 0.598795 0.718378 0.862045 0.246602 0.424957 0.643488 0.185057 0.187388 -0.310532 0.657389 0.213720 -0.738147 -0.319659 0.644451 0.654831 NaN 0.789514 0.862082 NaN -0.121353 0.187128 NaN -0.667363 NaN 0.118624 -0.024330 0.662925 -0.482323 -0.483702 0.793669 0.640322 0.273738 0.554704 0.670760 0.300075 0.101276 0.084311 -0.266180 -0.035225 0.001327 0.613202 -0.482571 0.179762 0.182013 0.048316 -0.626715 0.785873 0.228111 0.778501 0.704478 0.934762 0.760928 0.836165 0.829813 -0.285385
nonInterestIncome 0.601514 0.779621 0.617093 0.753330 0.270753 0.772286 0.872248 0.848231 0.537092 0.896243 0.546748 0.349018 0.584603 0.787460 0.692213 0.107901 0.841110 0.862619 0.844775 0.858159 0.848945 0.292374 0.690086 0.483046 0.767181 0.206232 0.763752 0.790384 0.719047 0.728663 0.803561 0.781659 0.306602 0.997996 0.207886 0.452702 0.706573 0.834230 0.907186 0.913795 0.896557 0.893131 0.556643 0.660501 0.606406 0.837651 -0.716228 0.689349 0.716323 1.000000 -0.041014 0.779550 0.693040 0.879654 0.752447 0.716067 0.881002 0.875376 0.882496 0.894631 0.878474 0.865574 0.742558 0.058494 -0.048348 0.693190 0.726787 0.472391 0.400872 -0.101235 0.881106 0.143349 -0.911149 0.060482 0.885506 0.889441 NaN 0.700915 0.594047 NaN -0.157572 0.120995 NaN -0.895100 NaN 0.023885 -0.219294 0.878474 -0.572108 -0.572177 0.719265 0.754714 0.408192 0.598379 0.890698 0.438836 0.403575 0.459711 0.020823 -0.068307 -0.146892 0.651932 -0.418951 0.201749 0.213795 -0.096394 -0.912695 0.870419 -0.228572 0.840399 0.710880 0.758041 0.598950 0.926919 0.920105 -0.325193
otherNonOperatingIncome 0.083645 -0.210226 -0.026464 -0.107422 0.083655 -0.217189 -0.146425 -0.519191 0.102330 -0.072331 0.045561 -0.224483 0.099048 -0.209075 -0.515727 0.099086 -0.255152 -0.124342 -0.305357 -0.272698 -0.399268 -0.080879 -0.360848 -0.493270 -0.406204 -0.116643 -0.267432 -0.089740 -0.342258 -0.323639 -0.021481 -0.381849 0.007540 -0.999350 0.002538 -0.018087 -0.091753 -0.101777 -0.213757 -0.284765 -0.273602 -0.218218 0.077075 0.098313 0.085533 -0.339038 0.166028 -0.192122 -0.180757 -0.041014 1.000000 -0.003785 -0.212850 -0.210859 -0.383103 -0.165408 -0.163145 -0.168894 -0.212986 -0.204175 -0.166341 -0.238506 -0.005417 -0.246121 -0.181947 0.041363 -0.088585 0.014567 0.007593 0.304043 -0.163297 0.384678 -0.011822 -0.264320 -0.061481 -0.070133 NaN -0.183555 -0.365533 NaN 0.196006 -0.425850 NaN 0.116396 NaN -0.028917 -0.140920 -0.166341 0.253276 0.252896 -0.211694 -0.172540 -0.089363 -0.579108 -0.223317 0.097046 0.097356 0.083214 0.172797 0.012048 0.161611 -0.022470 0.279729 -0.062140 -0.052715 0.258907 0.321370 -0.108016 0.155550 -0.371210 -0.460608 -0.295774 -0.281261 -0.206320 -0.195712 0.139299
depreciation 0.837099 0.906458 0.848317 0.733337 0.614761 0.474887 0.760773 0.711656 0.828313 0.894659 0.632174 0.431656 0.660783 0.591109 0.235625 0.425678 0.783259 0.504993 0.698409 0.682862 0.478917 0.439174 0.347169 0.298977 0.662498 0.481096 0.584366 0.573790 0.449188 0.475523 0.603665 0.415273 0.720247 NaN 0.618557 0.449759 0.408791 0.840610 0.741844 0.650776 0.617588 0.758644 0.782217 0.803981 0.805753 0.755733 -0.600324 0.568280 0.600524 0.779550 -0.003785 1.000000 0.633513 0.759413 0.604222 0.600324 0.762772 0.758914 0.763921 0.772103 0.764295 0.838940 0.684197 -0.354038 -0.149331 0.458845 0.978548 0.799046 0.305690 -0.089457 0.762772 -0.010278 -0.696184 -0.143505 0.621803 0.621803 NaN 0.880220 0.508548 NaN -0.226865 0.170322 NaN -0.668826 NaN 0.074244 -0.223753 0.764295 -0.678025 -0.676792 0.400040 0.354992 0.383614 0.267755 0.758662 0.484796 0.532687 0.618489 0.221797 -0.282701 -0.147560 0.315488 -0.525920 -0.132898 0.130640 0.294222 -0.567716 0.745099 0.172581 0.456861 0.466263 0.575749 0.364632 0.730860 0.682360 -0.382873
depreciationAndAmortization 0.373598 0.725002 0.603809 0.702857 0.333252 0.609793 0.781245 0.735043 0.513031 0.786865 0.179828 0.145471 0.188094 0.754024 0.569729 0.193741 0.668064 0.640480 0.686795 0.699115 0.678758 0.060546 0.516110 0.321940 0.604145 0.014218 0.562212 0.485072 0.509049 0.572454 0.876594 0.633264 0.434434 0.725820 0.393310 0.446477 0.552448 0.742058 0.852312 0.842517 0.858986 0.779647 0.543980 0.548278 0.534342 0.767215 -0.471712 0.574297 0.477551 0.693040 -0.212850 0.633513 1.000000 0.786057 0.662635 0.471435 0.785945 0.786261 0.785150 0.807963 0.785201 0.782083 0.642605 -0.597005 -0.003803 0.487059 0.602827 0.391615 0.319179 0.025759 0.785879 0.030902 -0.793200 -0.039241 0.836814 0.841676 NaN 0.492747 0.404947 NaN -0.230578 0.188380 NaN -0.852547 NaN 0.097117 -0.435625 0.785201 -0.465360 -0.465402 0.546687 0.601055 0.343348 0.367252 0.825635 0.141911 0.289497 0.379799 0.006231 -0.071663 -0.248153 0.429477 -0.345581 0.166657 0.180486 0.084964 -0.776115 0.782892 -0.174555 0.686539 0.513227 0.554502 0.453293 0.742887 0.734147 -0.307256
incomeBeforeTax 0.459875 0.903459 0.771185 0.770306 0.470582 0.788509 0.948434 0.805118 0.624117 0.925893 0.591926 0.522112 0.592149 0.777752 0.566995 0.320551 0.911096 0.809080 0.872965 0.911313 0.804027 0.409829 0.645192 0.476413 0.781026 0.349772 0.706607 0.715689 0.682486 0.654284 0.837545 0.730776 0.518128 -0.997647 0.370377 0.633672 0.666766 0.954739 0.969972 0.913382 0.893997 0.997891 0.703789 0.698986 0.700752 0.797428 -0.663584 0.637227 0.667355 0.879654 -0.210859 0.759413 0.786057 1.000000 0.866718 0.663052 0.993341 0.990607 0.999598 0.995937 0.993493 0.960402 0.690945 -0.501966 0.102253 0.742837 0.779026 0.563940 0.517768 -0.023096 0.993353 -0.153516 -0.883957 0.154495 0.873252 0.875122 NaN 0.696240 0.661248 NaN -0.163396 0.043861 NaN -0.882315 NaN -0.031642 -0.031867 0.993493 -0.622691 -0.622999 0.646791 0.819174 0.550019 0.503022 0.995909 0.479009 0.522559 0.529840 0.104630 -0.101582 -0.254768 0.551304 -0.416315 0.327102 0.338009 0.087324 -0.887082 0.932130 -0.202967 0.792321 0.614024 0.705186 0.629989 0.930859 0.924851 -0.442633
incomeTaxExpense 0.267627 0.789921 0.646043 0.633788 0.383691 0.733866 0.809860 0.804796 0.439330 0.734735 0.378491 0.462944 0.352332 0.688563 0.629411 0.260781 0.794354 0.684134 0.785365 0.768826 0.768045 0.287101 0.621346 0.493315 0.724611 0.305345 0.634205 0.640282 0.631328 0.594091 0.687013 0.680074 0.421966 0.999881 0.315418 0.539129 0.531597 0.795284 0.846277 0.830310 0.807370 0.866092 0.548668 0.506979 0.526608 0.762469 -0.565214 0.623797 0.569916 0.752447 -0.383103 0.604222 0.662635 0.866718 1.000000 0.564598 0.805010 0.804762 0.864479 0.866373 0.804267 0.840278 0.451850 -0.493311 0.146416 0.634741 0.614655 0.412188 0.440357 -0.075161 0.805065 -0.220658 -0.708403 0.219027 0.684152 0.697530 NaN 0.446948 0.632692 NaN -0.267313 0.170090 NaN -0.722243 NaN 0.009983 0.393282 0.804267 -0.592201 -0.592939 0.574126 0.711585 0.488326 0.580925 0.861957 0.302796 0.324257 0.366107 -0.006783 -0.096027 -0.311585 0.443089 -0.401820 0.311717 0.304110 0.066942 -0.777734 0.778388 -0.253345 0.748914 0.651010 0.638247 0.596119 0.794069 0.788262 -0.449911
interestAndDebtExpense 0.331050 0.684985 0.649979 0.558381 0.434527 0.856605 0.775201 0.494609 0.192181 0.762268 0.708383 0.779312 0.665872 0.736318 0.421410 0.362659 0.747958 0.822829 0.925483 0.845085 0.771981 0.564096 0.808128 0.548277 0.921621 0.535723 0.942850 0.862553 0.939384 0.826442 0.448092 0.755505 0.055745 -0.999728 -0.122750 0.599381 0.649661 0.582100 0.658136 0.708897 0.657806 0.674196 0.346280 0.306952 0.334405 0.850035 -0.999989 0.651156 0.999988 0.716067 -0.165408 0.600324 0.471435 0.663052 0.564598 1.000000 0.652903 0.657143 0.683293 0.660335 0.658609 0.593249 0.717982 0.862045 0.241059 0.427580 0.639935 0.168736 0.192418 -0.327336 0.652989 0.219117 -0.734963 -0.319659 0.644027 0.654437 NaN 0.789514 0.861393 NaN -0.149813 0.187113 NaN -0.662867 NaN 0.121517 -0.024330 0.658609 -0.496484 -0.498034 0.792216 0.644380 0.283651 0.542067 0.666533 0.288060 0.085602 0.065854 -0.289923 -0.039003 -0.011877 0.610350 -0.474480 0.184340 0.186262 0.034365 -0.624433 0.783665 0.214519 0.778793 0.731317 0.934666 0.759782 0.835227 0.828291 -0.301778
netIncomeFromContinuingOperations 0.487005 0.892916 0.765822 0.774740 0.464909 0.768547 0.943662 0.775783 0.643723 0.934267 0.607382 0.497668 0.615264 0.766813 0.527657 0.312946 0.902948 0.807452 0.856484 0.908512 0.782739 0.423886 0.612384 0.443045 0.759291 0.347124 0.690990 0.704266 0.658515 0.640475 0.841841 0.715401 0.520539 -0.997707 0.371824 0.625317 0.668818 0.954904 0.962090 0.899156 0.880988 0.990890 0.710245 0.716205 0.712519 0.778251 -0.653394 0.619782 0.657305 0.881002 -0.163145 0.762772 0.785945 0.993341 0.805010 0.652903 1.000000 0.996240 0.993189 0.988554 0.999650 0.951899 0.717009 -0.506499 0.072131 0.741848 0.785549 0.577944 0.517725 -0.005869 0.999999 -0.126860 -0.893564 0.128259 0.876446 0.878879 NaN 0.700657 0.637581 NaN -0.124933 0.011263 NaN -0.886062 NaN -0.039212 -0.162601 0.999650 -0.603506 -0.603685 0.636427 0.811865 0.542549 0.461675 0.989588 0.502071 0.549130 0.548439 0.127746 -0.098515 -0.230840 0.555822 -0.396249 0.316744 0.331697 0.082644 -0.881496 0.928301 -0.186384 0.770544 0.579252 0.687622 0.606711 0.926130 0.920581 -0.422438
comprehensiveIncomeNetOfTax 0.482524 0.895726 0.776318 0.786831 0.479876 0.769816 0.943389 0.776283 0.640395 0.933910 0.598102 0.501565 0.605631 0.770530 0.527419 0.324550 0.891194 0.810226 0.859523 0.909638 0.783113 0.422189 0.616952 0.445907 0.763845 0.335915 0.696240 0.703859 0.665853 0.636843 0.844755 0.717263 0.522014 -0.994021 0.368884 0.632402 0.669801 0.952463 0.961003 0.898478 0.880892 0.987522 0.710389 0.715628 0.712320 0.789868 -0.657647 0.646232 0.661487 0.875376 -0.168894 0.758914 0.786261 0.990607 0.804762 0.657143 0.996240 1.000000 0.990338 0.986005 0.996449 0.949703 0.707015 -0.472767 0.080045 0.735200 0.784833 0.570844 0.504553 0.000075 0.996253 -0.121123 -0.888658 0.111537 0.874486 0.876788 NaN 0.703749 0.640679 NaN -0.134460 0.008543 NaN -0.884064 NaN -0.010121 -0.135446 0.996449 -0.607472 -0.607649 0.634804 0.809567 0.545224 0.465754 0.986592 0.505920 0.546258 0.544444 0.126164 -0.099145 -0.231036 0.561559 -0.406986 0.319972 0.335034 0.096819 -0.874672 0.929241 -0.184691 0.772459 0.585578 0.692774 0.614170 0.928162 0.922408 -0.427174
ebit 0.461268 0.907585 0.777133 0.772446 0.476376 0.797547 0.952905 0.805427 0.618141 0.930646 0.605541 0.539878 0.604329 0.786165 0.571040 0.327294 0.916991 0.814402 0.884237 0.918204 0.810203 0.420516 0.658070 0.483969 0.795264 0.360231 0.722504 0.727464 0.700146 0.668513 0.832963 0.739684 0.510388 -0.997575 0.359634 0.640841 0.673654 0.953150 0.970290 0.916533 0.896009 0.997785 0.701108 0.694455 0.697471 0.805749 -0.683812 0.644998 0.687256 0.882496 -0.212986 0.763921 0.785150 0.999598 0.864479 0.683293 0.993189 0.990338 1.000000 0.995691 0.993525 0.959333 0.701202 -0.498887 0.108645 0.739798 0.784338 0.558739 0.513119 -0.033342 0.993202 -0.143960 -0.887510 0.136052 0.875223 0.877018 NaN 0.710314 0.676194 NaN -0.163164 0.056825 NaN -0.883865 NaN -0.025673 -0.031880 0.993525 -0.625260 -0.625608 0.656596 0.820840 0.546922 0.512227 0.995702 0.477633 0.514060 0.520847 0.093144 -0.100567 -0.249302 0.555185 -0.424229 0.325980 0.336754 0.088156 -0.887045 0.937629 -0.190127 0.799640 0.624489 0.720737 0.641385 0.935931 0.929241 -0.442578
ebitda 0.463889 0.914932 0.785145 0.778985 0.486905 0.789872 0.956693 0.820462 0.637961 0.934683 0.580991 0.519320 0.581261 0.800814 0.577621 0.336695 0.910307 0.804648 0.874205 0.908872 0.803469 0.387773 0.646424 0.464941 0.779975 0.328039 0.704481 0.713507 0.676992 0.656475 0.859632 0.730310 0.538439 -0.999760 0.398771 0.642227 0.673523 0.957865 0.981230 0.926507 0.910462 0.994444 0.716732 0.709629 0.711469 0.810664 -0.660868 0.660139 0.664703 0.894631 -0.204175 0.772103 0.807963 0.995937 0.866373 0.660335 0.988554 0.986005 0.995691 1.000000 0.988731 0.964669 0.693594 -0.514497 0.094038 0.729612 0.790779 0.576847 0.501919 -0.006036 0.988545 -0.148201 -0.889888 0.133200 0.883908 0.885174 NaN 0.681128 0.649986 NaN -0.174761 0.077563 NaN -0.891922 NaN -0.012176 -0.026329 0.988731 -0.621692 -0.622060 0.644528 0.810757 0.540313 0.495046 0.995502 0.447308 0.502552 0.527159 0.101013 -0.102605 -0.269233 0.542003 -0.435704 0.320785 0.332069 0.110711 -0.888241 0.942878 -0.200264 0.793556 0.610686 0.701954 0.624276 0.931068 0.923176 -0.442891
netIncome 0.486785 0.896009 0.771272 0.773023 0.473039 0.771857 0.945040 0.775450 0.643256 0.935606 0.614238 0.509689 0.620988 0.769130 0.525808 0.322358 0.904096 0.807504 0.860719 0.910183 0.782541 0.425624 0.620607 0.454468 0.765056 0.347075 0.696092 0.702279 0.665106 0.643516 0.840977 0.715358 0.520946 -0.997707 0.369245 0.631852 0.672999 0.955881 0.962385 0.898609 0.880752 0.991123 0.713211 0.717007 0.714629 0.778372 -0.659103 0.618307 0.662925 0.878474 -0.166341 0.764295 0.785201 0.993493 0.804267 0.658609 0.999650 0.996449 0.993525 0.988731 1.000000 0.952353 0.719904 -0.506499 0.088392 0.740078 0.787780 0.577758 0.516318 -0.010118 0.999651 -0.132514 -0.891389 0.129975 0.876908 0.879183 NaN 0.707858 0.643341 NaN -0.129927 0.011263 NaN -0.886272 NaN -0.039237 -0.155605 1.000000 -0.606650 -0.606848 0.639491 0.813480 0.543787 0.464382 0.989706 0.501551 0.548535 0.547654 0.126205 -0.099098 -0.232382 0.555648 -0.402936 0.318532 0.333263 0.088753 -0.879281 0.929995 -0.183270 0.770489 0.580905 0.693480 0.613614 0.927707 0.921874 -0.424620
operatingCashflow 0.464251 0.919670 0.793247 0.777753 0.518842 0.726010 0.924838 0.816055 0.690988 0.906616 0.553240 0.488514 0.553078 0.766555 0.544098 0.369994 0.886751 0.717861 0.833337 0.860771 0.740629 0.374862 0.573425 0.472342 0.743053 0.330695 0.651812 0.625297 0.609833 0.591728 0.820483 0.674800 0.604852 -0.841941 0.458515 0.619587 0.641498 0.954306 0.951021 0.877019 0.860125 0.957146 0.760205 0.751663 0.761574 0.767520 -0.593894 0.637730 0.598795 0.865574 -0.238506 0.838940 0.782083 0.960402 0.840278 0.593249 0.951899 0.949703 0.959333 0.964669 0.952353 1.000000 0.670658 -0.552560 0.130952 0.672424 0.793357 0.648821 0.486868 0.017915 0.951890 -0.207567 -0.851817 0.236683 0.867873 0.867658 NaN 0.698920 0.625797 NaN -0.206799 0.084523 NaN -0.875592 NaN -0.038046 -0.083099 0.952353 -0.640022 -0.640168 0.566303 0.763770 0.552789 0.541265 0.958710 0.472072 0.570755 0.608141 0.206356 -0.114227 -0.316586 0.446489 -0.487480 0.341229 0.352820 0.178040 -0.832004 0.902652 -0.238452 0.725829 0.572103 0.653909 0.615728 0.888605 0.870004 -0.450437
paymentsForOperatingActivities 0.469564 0.692238 0.659251 0.696764 0.426205 0.631277 0.746864 0.429629 0.518570 0.814135 0.642195 0.487830 0.653007 0.612993 0.270376 0.291291 0.683660 0.744149 0.729433 0.704485 0.590673 0.325836 0.530510 0.375241 0.673252 0.276586 0.671915 0.631983 0.649004 0.613607 0.638538 0.574546 0.303349 0.978822 0.152015 0.501251 0.619851 0.711721 0.712461 0.666050 0.652804 0.696995 0.552068 0.622794 0.599221 0.668657 -0.718302 0.516206 0.718378 0.742558 -0.005417 0.684197 0.642605 0.690945 0.451850 0.717982 0.717009 0.707015 0.701202 0.693594 0.719904 0.670658 1.000000 -0.905086 0.065003 0.457256 0.708362 0.415599 0.236736 -0.127462 0.716778 0.112969 -0.746707 -0.173223 0.711150 0.722981 NaN 0.567958 0.514801 NaN -0.129368 -0.084842 NaN -0.714256 NaN -0.082865 -0.482975 0.719904 -0.406062 -0.406614 0.581440 0.650897 0.387433 0.238411 0.707423 0.447033 0.383020 0.421082 0.084235 0.030729 -0.075088 0.495978 -0.384475 0.253235 0.258242 0.145932 -0.614390 0.802054 -0.066466 0.639064 0.490453 0.662266 0.605400 0.773847 0.762143 -0.315276
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changeInOperatingAssets 0.341367 0.621824 0.502647 0.414730 0.285166 0.629891 0.697635 0.489712 0.434685 0.666445 0.480429 0.365951 0.490430 0.508971 0.346758 0.227307 0.640720 0.611237 0.612560 0.670939 0.576821 0.316058 0.438622 0.318126 0.487398 0.302752 0.463162 0.534462 0.470184 0.469459 0.628293 0.459810 0.339415 -0.972253 0.241226 0.475233 0.478114 0.686084 0.693361 0.647169 0.636922 0.739055 0.476565 0.475120 0.468473 0.468128 -0.427856 0.405964 0.424957 0.693190 0.041363 0.458845 0.487059 0.742837 0.634741 0.427580 0.741848 0.735200 0.739798 0.729612 0.740078 0.672424 0.457256 -0.973394 0.126241 1.000000 0.504985 0.367474 0.850447 0.116061 0.741841 -0.129935 -0.650228 0.395636 0.612574 0.624394 NaN 0.359162 0.413099 NaN -0.012132 -0.036911 NaN -0.632947 NaN -0.226771 0.132959 0.740078 -0.396329 -0.396926 0.495272 0.618453 0.369859 0.176497 0.725870 0.354503 0.335572 0.326136 0.016674 -0.051277 -0.104282 0.497770 -0.078229 0.202915 0.210166 -0.031700 -0.672550 0.628505 -0.152962 0.515351 0.345230 0.462462 0.384888 0.654706 0.659436 -0.284574
depreciationDepletionAndAmortization 0.617497 0.917406 0.923207 0.761470 0.781126 0.570839 0.845687 0.588569 0.818621 0.902902 0.758371 0.508635 0.777651 0.651926 0.183563 0.665061 0.771069 0.559837 0.758735 0.734643 0.472820 0.502630 0.378549 0.298038 0.713024 0.543069 0.619255 0.562269 0.552649 0.516325 0.673142 0.445377 0.705619 0.928897 0.506801 0.676563 0.486340 0.868048 0.760254 0.627567 0.609460 0.766576 0.844762 0.840910 0.855209 0.789272 -0.640493 0.660250 0.643488 0.726787 -0.088585 0.978548 0.602827 0.779026 0.614655 0.639935 0.785549 0.784833 0.784338 0.790779 0.787780 0.793357 0.708362 -0.484440 0.087703 0.504985 1.000000 0.800115 0.340550 0.186092 0.785481 -0.146025 -0.717972 -0.135314 0.629684 0.646152 NaN 0.745630 0.557880 NaN -0.078558 0.219704 NaN -0.682857 NaN 0.105571 -0.136560 0.787780 -0.483597 -0.483582 0.390436 0.534376 0.430487 0.286560 0.764928 0.594478 0.639429 0.679816 0.396664 -0.083234 -0.187296 0.286535 -0.518822 0.312597 0.327282 0.514825 -0.512977 0.839608 0.047502 0.458937 0.298106 0.608916 0.548042 0.774465 0.732232 -0.338684
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changeInInventory 0.238220 0.066160 0.162022 0.117308 0.265702 -0.200470 -0.021414 -0.090620 0.394361 -0.013761 -0.072877 -0.335741 -0.025644 -0.072280 -0.135673 0.230974 -0.220074 -0.159326 -0.210994 -0.194264 -0.228477 -0.327158 -0.304550 -0.337312 -0.284803 -0.334217 -0.333325 -0.274251 -0.370495 -0.279678 0.247977 -0.256195 0.470080 NaN 0.507240 -0.098577 -0.334553 0.081913 0.018074 -0.080490 -0.029071 -0.071082 0.300209 0.318910 0.288079 -0.144594 0.327336 -0.019626 -0.310532 -0.101235 0.304043 -0.089457 0.025759 -0.023096 -0.075161 -0.327336 -0.005869 0.000075 -0.033342 -0.006036 -0.010118 0.017915 -0.127462 0.014909 -0.196212 0.116061 0.186092 0.435141 0.171691 1.000000 -0.005953 -0.162771 0.058169 -0.038086 -0.099802 -0.099802 NaN -0.444209 -0.417614 NaN -0.166751 0.326374 NaN 0.032998 NaN 0.171804 -0.010914 -0.010118 0.154299 0.154992 -0.257852 -0.181111 -0.085219 -0.428400 -0.060593 0.054105 0.271836 0.407727 0.519829 -0.108176 -0.148645 -0.139151 0.182819 -0.186259 -0.011010 0.452269 0.154528 -0.087196 -0.167708 -0.264279 -0.420068 -0.345313 -0.469745 -0.118732 -0.133461 0.250323
profitLoss 0.487075 0.892865 0.765691 0.774620 0.464742 0.768613 0.943640 0.775802 0.643645 0.934280 0.607292 0.497509 0.615191 0.766818 0.527723 0.312798 0.902937 0.807468 0.856563 0.908552 0.782798 0.423975 0.612428 0.443119 0.759405 0.347124 0.691104 0.704162 0.658663 0.640555 0.841773 0.715479 0.520332 -0.997707 0.371560 0.625241 0.668984 0.954876 0.962076 0.899166 0.880983 0.990898 0.710155 0.716130 0.712448 0.778251 -0.653480 0.619855 0.657389 0.881106 -0.163297 0.762772 0.785879 0.993353 0.805065 0.652989 0.999999 0.996253 0.993202 0.988545 0.999651 0.951890 0.716778 -0.506499 0.072280 0.741841 0.785481 0.577885 0.517670 -0.005953 1.000000 -0.126698 -0.893598 0.128259 0.876519 0.878955 NaN 0.701314 0.637719 NaN -0.124933 0.011263 NaN -0.886129 NaN -0.038983 -0.160460 0.999651 -0.603564 -0.603743 0.636534 0.811825 0.542453 0.461879 0.989587 0.502165 0.549147 0.548439 0.127664 -0.098465 -0.230632 0.555906 -0.396208 0.316655 0.331598 0.082406 -0.881579 0.928291 -0.186349 0.770576 0.579331 0.687736 0.606774 0.926205 0.920646 -0.422338
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proceedsFromRepaymentsOfShortTermDebt -0.024913 0.041203 -0.186963 -0.235453 -0.268323 0.116536 0.066016 0.191875 -0.044083 -0.016601 -0.459935 -0.293029 -0.467514 -0.047684 0.229159 -0.194053 0.213944 0.031241 0.027800 0.158226 0.133290 -0.018531 0.208424 0.397812 -0.045030 -0.260824 -0.101707 -0.085930 -0.091539 0.021846 0.140585 0.072260 0.073129 NaN 0.073050 -0.027625 0.107880 0.124677 0.128990 0.099191 0.110629 0.157444 -0.040461 -0.019749 -0.016760 -0.157478 0.319659 -0.279784 -0.319659 0.060482 -0.264320 -0.143505 -0.039241 0.154495 0.219027 -0.319659 0.128259 0.111537 0.136052 0.133200 0.129975 0.236683 -0.173223 NaN 0.171438 0.395636 -0.135314 0.006905 0.361637 -0.038086 0.128259 -0.454593 0.036007 1.000000 0.102173 0.102173 NaN 0.010677 0.026847 NaN -0.186254 0.207053 NaN -0.105706 NaN -0.558029 -0.308050 0.129975 -0.092207 -0.092030 0.077665 0.152134 0.111942 0.134710 0.135136 -0.053395 0.000732 0.018434 -0.045475 -0.176582 -0.141628 0.086825 0.065902 -0.071403 -0.057541 -0.442956 -0.233693 0.004242 -0.194296 0.066815 0.029164 -0.059194 -0.028864 0.061804 0.066422 -0.143250
paymentsForRepurchaseOfCommonStock 0.474387 0.752656 0.574776 0.721029 0.170551 0.764632 0.878504 0.630093 0.446930 0.880697 0.276127 0.129549 0.302223 0.819633 0.562511 0.014505 0.749519 0.823101 0.819616 0.820145 0.826266 0.115638 0.688923 0.467383 0.711516 -0.050628 0.740343 0.715211 0.666579 0.711982 0.864609 0.773980 0.198481 0.673567 0.109486 0.403715 0.687691 0.833796 0.926757 0.895937 0.902273 0.875981 0.515418 0.587835 0.543788 0.763662 -0.644364 0.615154 0.644451 0.885506 -0.061481 0.621803 0.836814 0.873252 0.684152 0.644027 0.876446 0.874486 0.875223 0.883908 0.876908 0.867873 0.711150 NaN 0.008853 0.612574 0.629684 0.323022 0.355088 -0.099802 0.876519 0.283586 -0.954160 0.102173 1.000000 1.000000 NaN 0.613196 0.509526 NaN -0.096763 0.026392 NaN -0.999566 NaN -0.026830 -0.038727 0.876908 -0.529690 -0.529873 0.727299 0.795022 0.508753 0.411993 0.895195 0.264162 0.319236 0.394511 -0.083617 0.242545 -0.104946 0.632241 -0.357588 0.171348 0.218932 -0.177699 -0.892548 0.873947 -0.147411 0.823257 0.617528 0.738909 0.663583 0.901112 0.895601 -0.459862
paymentsForRepurchaseOfEquity 0.471407 0.758621 0.594165 0.732318 0.218496 0.772874 0.881633 0.645592 0.470264 0.884881 0.314752 0.174758 0.338694 0.826206 0.579338 0.064563 0.759630 0.826291 0.826542 0.827028 0.831019 0.126869 0.688923 0.475717 0.723077 -0.026458 0.745659 0.722316 0.666579 0.720177 0.869281 0.781168 0.243511 0.673567 0.143532 0.431299 0.698411 0.835221 0.926989 0.899763 0.905849 0.877988 0.539612 0.606325 0.565755 0.774766 -0.654743 0.634606 0.654831 0.889441 -0.070133 0.621803 0.841676 0.875122 0.697530 0.654437 0.878879 0.876788 0.877018 0.885174 0.879183 0.867658 0.722981 NaN 0.036692 0.624394 0.646152 0.355512 0.371753 -0.099802 0.878955 0.232542 -0.955685 0.102173 1.000000 1.000000 NaN 0.613196 0.526840 NaN -0.096763 0.026392 NaN -0.999524 NaN -0.019190 -0.038727 0.879183 -0.547847 -0.548091 0.735571 0.774773 0.399731 0.440024 0.896639 0.291215 0.355268 0.423522 -0.043837 0.260862 -0.155980 0.632261 -0.373902 0.201929 0.210482 -0.123761 -0.894903 0.876040 -0.180577 0.825902 0.620779 0.744367 0.668440 0.904737 0.899353 -0.324436
paymentsForRepurchaseOfPreferredStock NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
dividendPayout 0.675077 0.845764 0.739469 0.482579 0.310418 0.701916 0.772265 0.518286 0.577639 0.803258 0.660852 0.706715 0.636456 0.488102 0.258796 0.173689 0.819865 0.590927 0.842960 0.820569 0.562194 0.645125 0.580263 0.407778 0.824367 0.586456 0.725615 0.523946 0.723330 0.556024 0.459543 0.542988 0.083056 NaN -0.156287 0.566079 0.567601 0.722861 0.615143 0.583937 0.505993 0.693512 0.553937 0.583294 0.592048 0.596289 -0.789514 0.345755 0.789514 0.700915 -0.183555 0.880220 0.492747 0.696240 0.446948 0.789514 0.700657 0.703749 0.710314 0.681128 0.707858 0.698920 0.567958 NaN 0.019880 0.359162 0.745630 0.513570 0.145947 -0.444209 0.701314 0.253144 -0.641803 0.010677 0.613196 0.613196 NaN 1.000000 0.999952 NaN -0.029996 0.099725 NaN -0.606678 NaN 0.073363 -0.053396 0.707858 -0.725209 -0.725606 0.577360 0.462371 0.329950 0.541220 0.685276 0.601011 0.539185 0.439191 -0.312143 0.525210 0.627939 0.516069 -0.381350 0.274057 0.343075 -0.243944 -0.546045 0.759887 0.337595 0.530249 0.562823 0.719493 0.697632 0.757298 0.723516 -0.353359
dividendPayoutCommonStock 0.204936 0.679996 0.626104 0.451032 0.427611 0.822414 0.727233 0.617822 0.134031 0.690076 0.644922 0.819425 0.590063 0.638486 0.452770 0.367559 0.807822 0.665025 0.873686 0.839106 0.708887 0.744915 0.731666 0.565665 0.887726 0.713037 0.827615 0.708808 0.829487 0.710379 0.332062 0.730754 0.090606 NaN -0.126570 0.697527 0.664886 0.569586 0.608607 0.656841 0.584541 0.673841 0.353801 0.227358 0.307661 0.790202 -0.861557 0.538582 0.862082 0.594047 -0.365533 0.508548 0.404947 0.661248 0.632692 0.861393 0.637581 0.640679 0.676194 0.649986 0.643341 0.625797 0.514801 NaN 0.392026 0.413099 0.557880 0.144991 0.191895 -0.417614 0.637719 0.006019 -0.596725 0.026847 0.509526 0.526840 NaN 0.999952 1.000000 NaN -0.122380 0.432997 NaN -0.555215 NaN 0.063411 -0.026439 0.643341 -0.570233 -0.571983 0.669299 0.598497 0.319299 0.778007 0.656999 0.301034 0.057103 0.000023 -0.340845 -0.052807 -0.033426 0.480775 -0.552927 0.222964 0.219970 -0.043371 -0.596689 0.716712 0.239866 0.702300 0.736772 0.827259 0.725539 0.736271 0.725793 -0.344214
dividendPayoutPreferredStock NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
proceedsFromIssuanceOfCommonStock -0.091109 -0.215399 -0.132384 -0.161948 -0.090430 -0.209305 -0.119055 -0.278875 0.000851 -0.073156 0.018459 -0.148183 0.044313 -0.276931 -0.507331 -0.064463 -0.113339 -0.074269 -0.189476 -0.128978 -0.263109 0.098968 -0.357346 -0.291815 -0.220191 0.006856 -0.254755 -0.143629 -0.439226 -0.279188 -0.234436 -0.254825 -0.213350 NaN -0.237943 0.037340 0.022519 -0.126415 -0.242549 -0.262949 -0.275417 -0.161139 -0.044561 -0.014333 -0.022206 -0.244344 0.149813 -0.061155 -0.121353 -0.157572 0.196006 -0.226865 -0.230578 -0.163396 -0.267313 -0.149813 -0.124933 -0.134460 -0.163164 -0.174761 -0.129927 -0.206799 -0.129368 0.186284 -0.145647 -0.012132 -0.078558 -0.063514 -0.007052 -0.166751 -0.124933 0.135856 0.090129 -0.186254 -0.096763 -0.096763 NaN -0.029996 -0.122380 NaN 1.000000 -0.304881 NaN 0.204063 NaN -0.035061 0.360434 -0.129927 0.310959 0.311185 -0.150958 -0.137383 -0.231989 -0.357473 -0.174209 0.086694 0.000194 -0.122572 -0.051191 0.858022 0.259569 0.025577 -0.168692 -0.270370 -0.240221 -0.058793 0.196407 0.269499 0.479923 -0.167147 -0.181337 -0.269471 0.131316 -0.134956 -0.120915 0.457471
proceedsFromIssuanceOfLongTermDebtAndCapitalSecuritiesNet -0.200287 0.427393 0.198928 0.085689 0.230802 0.197483 0.084855 0.629448 -0.182428 -0.046197 -0.322412 0.318240 -0.325138 0.294328 0.651388 0.245550 0.312161 -0.116396 0.283679 0.139120 0.189674 0.189913 0.191521 0.269672 0.474686 0.249855 0.152167 -0.580449 0.169437 0.364807 -0.027566 0.326336 0.234744 NaN 0.291619 0.083800 0.095601 -0.084260 0.143043 0.229530 0.253647 0.028870 -0.209663 -0.262385 -0.248921 0.365355 -0.187113 0.501661 0.187128 0.120995 -0.425850 0.170322 0.188380 0.043861 0.170090 0.187113 0.011263 0.008543 0.056825 0.077563 0.011263 0.084523 -0.084842 NaN -0.009276 -0.036911 0.219704 -0.017428 -0.087484 0.326374 0.011263 -0.376332 0.176196 0.207053 0.026392 0.026392 NaN 0.099725 0.432997 NaN -0.304881 1.000000 NaN -0.021441 NaN -0.026460 NaN 0.011263 -0.359984 -0.362249 0.011742 -0.124389 -0.461979 0.648131 0.051397 -0.412116 -0.369792 -0.299622 -0.283570 -0.206225 -0.322955 -0.163740 -0.312941 -0.513193 -0.535993 0.040116 -0.104275 0.082538 0.165485 0.179369 0.363163 0.150722 0.022113 0.015879 -0.033467 -0.286544
proceedsFromIssuanceOfPreferredStock NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
proceedsFromRepurchaseOfEquity -0.524978 -0.778382 -0.635343 -0.754588 -0.304579 -0.781054 -0.887768 -0.674654 -0.525672 -0.892606 -0.370638 -0.228379 -0.393233 -0.837823 -0.591274 -0.157702 -0.774009 -0.828988 -0.836574 -0.834798 -0.832069 -0.157259 -0.711391 -0.501132 -0.742580 -0.025578 -0.758170 -0.734202 -0.685251 -0.728798 -0.882834 -0.789883 -0.328813 -0.682276 -0.210506 -0.477964 -0.709309 -0.846360 -0.930754 -0.903289 -0.910291 -0.884746 -0.591620 -0.651797 -0.615511 -0.789582 0.663107 -0.654418 -0.667363 -0.895100 0.116396 -0.668826 -0.852547 -0.882315 -0.722243 -0.662867 -0.886062 -0.884064 -0.883865 -0.891922 -0.886272 -0.875592 -0.714256 0.189807 -0.090306 -0.632947 -0.682857 -0.427875 -0.385703 0.032998 -0.886129 -0.155454 0.957416 -0.105706 -0.999566 -0.999524 NaN -0.606678 -0.555215 NaN 0.204063 -0.021441 NaN 1.000000 NaN 0.005404 0.070490 -0.886272 0.542766 0.542811 -0.744973 -0.766012 -0.399487 -0.467289 -0.902161 -0.340221 -0.420947 -0.490204 -0.039619 0.100888 0.199400 -0.628156 0.434179 -0.198764 -0.213568 0.024794 0.895564 -0.878891 0.131327 -0.827725 -0.603076 -0.757579 -0.623278 -0.911074 -0.905269 0.310840
proceedsFromSaleOfTreasuryStock NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
changeInCashAndCashEquivalents 0.015864 0.075760 0.106340 0.286307 0.074908 0.026576 0.049030 0.079687 0.031149 -0.002813 0.052607 0.040161 0.046330 0.120644 0.113237 0.027615 -0.004509 -0.057430 0.043713 0.014464 0.051540 -0.054481 0.058855 -0.011715 0.060488 0.042389 0.066163 -0.007952 0.061500 0.016112 0.026777 0.061420 0.086618 NaN 0.102622 -0.034623 -0.226628 -0.038337 -0.004444 0.026201 0.022839 -0.039476 -0.005802 -0.029641 -0.028591 0.214200 -0.121390 0.309732 0.118624 0.023885 -0.028917 0.074244 0.097117 -0.031642 0.009983 0.121517 -0.039212 -0.010121 -0.025673 -0.012176 -0.039237 -0.038046 -0.082865 0.391939 -0.051495 -0.226771 0.105571 0.092348 -0.100915 0.171804 -0.038983 0.360712 -0.014663 -0.558029 -0.026830 -0.019190 NaN 0.073363 0.063411 NaN -0.035061 -0.026460 NaN 0.005404 NaN 1.000000 -0.116498 -0.039237 -0.014189 -0.014206 -0.112343 -0.116611 0.004362 0.164460 -0.022731 -0.051818 -0.030393 -0.010042 0.034162 -0.003426 -0.048367 -0.182648 -0.070339 0.029021 0.031234 0.137697 0.062286 0.020009 0.008937 0.056960 0.139320 0.062334 0.016544 0.001368 -0.012850 -0.035138
changeInExchangeRate -0.051566 -0.095922 -0.088464 -0.338316 -0.058220 -0.022142 -0.076163 -0.142104 -0.145453 -0.096120 -0.099176 -0.147744 -0.083692 -0.116743 0.028250 -0.027784 -0.157673 -0.141734 -0.032747 -0.199537 -0.077922 -0.102250 -0.088470 -0.022186 0.005710 -0.137647 0.000845 0.057048 0.044360 -0.005894 -0.530352 0.010323 -0.157070 NaN -0.156675 -0.072172 0.080571 -0.064244 -0.097227 -0.126678 -0.124924 -0.013874 -0.097404 -0.134793 -0.117314 -0.184138 0.024330 0.025082 -0.024330 -0.219294 -0.140920 -0.223753 -0.435625 -0.031867 0.393282 -0.024330 -0.162601 -0.135446 -0.031880 -0.026329 -0.155605 -0.083099 -0.482975 0.809252 0.089401 0.132959 -0.136560 -0.186635 0.132096 -0.010914 -0.160460 -0.047259 0.093170 -0.308050 -0.038727 -0.038727 NaN -0.053396 -0.026439 NaN 0.360434 NaN NaN 0.070490 NaN -0.116498 1.000000 -0.155605 0.162749 0.162039 0.037772 -0.000148 0.001430 0.106204 -0.044253 0.049496 -0.021077 0.010112 0.015719 0.078167 0.036655 0.015816 0.062651 0.189331 -0.050409 0.046829 0.207529 -0.142094 -0.113304 -0.163391 -0.135230 -0.001811 0.083630 -0.039499 -0.049815 -0.032575
netIncome_cashflow 0.486785 0.896009 0.771272 0.773023 0.473039 0.771857 0.945040 0.775450 0.643256 0.935606 0.614238 0.509689 0.620988 0.769130 0.525808 0.322358 0.904096 0.807504 0.860719 0.910183 0.782541 0.425624 0.620607 0.454468 0.765056 0.347075 0.696092 0.702279 0.665106 0.643516 0.840977 0.715358 0.520946 -0.997707 0.369245 0.631852 0.672999 0.955881 0.962385 0.898609 0.880752 0.991123 0.713211 0.717007 0.714629 0.778372 -0.659103 0.618307 0.662925 0.878474 -0.166341 0.764295 0.785201 0.993493 0.804267 0.658609 0.999650 0.996449 0.993525 0.988731 1.000000 0.952353 0.719904 -0.506499 0.088392 0.740078 0.787780 0.577758 0.516318 -0.010118 0.999651 -0.132514 -0.891389 0.129975 0.876908 0.879183 NaN 0.707858 0.643341 NaN -0.129927 0.011263 NaN -0.886272 NaN -0.039237 -0.155605 1.000000 -0.606650 -0.606848 0.639491 0.813480 0.543787 0.464382 0.989706 0.501551 0.548535 0.547654 0.126205 -0.099098 -0.232382 0.555648 -0.402936 0.318532 0.333263 0.088753 -0.879281 0.929995 -0.183270 0.770489 0.580905 0.693480 0.613614 0.927707 0.921874 -0.424620
Current Ratio -0.186072 -0.645494 -0.565394 -0.490547 -0.400039 -0.584171 -0.618268 -0.592706 -0.363597 -0.573240 -0.222895 -0.307532 -0.205154 -0.612948 -0.624704 -0.319628 -0.632858 -0.434449 -0.637636 -0.622526 -0.556924 -0.352007 -0.531687 -0.465052 -0.610952 -0.362573 -0.563486 -0.507449 -0.577494 -0.527109 -0.465398 -0.517101 -0.353033 -0.999991 -0.239231 -0.574724 -0.441788 -0.616889 -0.640601 -0.614661 -0.595187 -0.620729 -0.541199 -0.417709 -0.485221 -0.605020 0.496637 -0.575362 -0.482323 -0.572108 0.253276 -0.678025 -0.465360 -0.622691 -0.592201 -0.496484 -0.603506 -0.607472 -0.625260 -0.621692 -0.606650 -0.640022 -0.406062 0.693584 -0.317772 -0.396329 -0.483597 -0.356135 -0.273814 0.154299 -0.603564 0.216048 0.502204 -0.092207 -0.529690 -0.547847 NaN -0.725209 -0.570233 NaN 0.310959 -0.359984 NaN 0.542766 NaN -0.014189 0.162749 -0.606650 1.000000 0.999988 -0.480632 -0.447094 -0.312066 -0.677294 -0.616589 -0.084340 -0.204843 -0.276828 0.100955 0.315127 0.445181 -0.234865 0.596517 -0.154607 -0.177582 -0.116532 0.561819 -0.615298 -0.069906 -0.553101 -0.674624 -0.569801 -0.386245 -0.561970 -0.548343 0.339453
Quick Ratio -0.183761 -0.646035 -0.566438 -0.490269 -0.401273 -0.586383 -0.619012 -0.593015 -0.362219 -0.573398 -0.223619 -0.309476 -0.205627 -0.614164 -0.624473 -0.321070 -0.633427 -0.435188 -0.638754 -0.623381 -0.557819 -0.352942 -0.533098 -0.465627 -0.612102 -0.363665 -0.564703 -0.507938 -0.579271 -0.528274 -0.465367 -0.518239 -0.352521 -0.999991 -0.238255 -0.576741 -0.443257 -0.616972 -0.641021 -0.615365 -0.595789 -0.621065 -0.541251 -0.416805 -0.484821 -0.605868 0.498190 -0.576856 -0.483702 -0.572177 0.252896 -0.676792 -0.465402 -0.622999 -0.592939 -0.498034 -0.603685 -0.607649 -0.625608 -0.622060 -0.606848 -0.640168 -0.406614 0.693584 -0.320097 -0.396926 -0.483582 -0.354802 -0.273826 0.154992 -0.603743 0.216178 0.502356 -0.092030 -0.529873 -0.548091 NaN -0.725606 -0.571983 NaN 0.311185 -0.362249 NaN 0.542811 NaN -0.014206 0.162039 -0.606848 0.999988 1.000000 -0.481434 -0.448563 -0.313317 -0.677477 -0.616896 -0.083084 -0.203228 -0.275014 0.102958 0.314571 0.446049 -0.235144 0.597114 -0.155729 -0.178597 -0.117086 0.561992 -0.616201 -0.069935 -0.554108 -0.676034 -0.570985 -0.388302 -0.562360 -0.548804 0.341055
Debt Equity Ratio 0.406854 0.480217 0.400622 0.470647 0.108469 0.837589 0.688236 0.421756 0.031808 0.659551 0.231462 0.420207 0.187802 0.657865 0.527779 0.003588 0.621212 0.884510 0.805463 0.757378 0.838749 0.220806 0.857352 0.537911 0.763780 0.026291 0.814164 0.835759 0.803033 0.772784 0.586692 0.800094 -0.200473 0.985567 -0.338802 0.429348 0.739944 0.532739 0.682253 0.763528 0.737444 0.661884 0.205047 0.252711 0.223765 0.608994 -0.791933 0.391860 0.793669 0.719265 -0.211694 0.400040 0.546687 0.646791 0.574126 0.792216 0.636427 0.634804 0.656596 0.644528 0.639491 0.566303 0.581440 0.225864 0.196954 0.495272 0.390436 -0.058229 0.176899 -0.257852 0.636534 0.273929 -0.748242 0.077665 0.727299 0.735571 NaN 0.577360 0.669299 NaN -0.150958 0.011742 NaN -0.744973 NaN -0.112343 0.037772 0.639491 -0.480632 -0.481434 1.000000 0.732204 0.222390 0.407742 0.663687 0.156640 -0.026071 0.009454 -0.417937 -0.072730 -0.019853 0.846290 -0.427525 0.100476 0.109417 -0.281610 -0.764049 0.687042 0.176954 0.838008 0.681171 0.811078 0.567448 0.798775 0.816261 -0.216684
ROE 0.176203 0.651823 0.573412 0.628844 0.297484 0.782384 0.767738 0.551530 0.286808 0.718115 0.445955 0.461661 0.430781 0.695300 0.506462 0.161622 0.708286 0.824858 0.770852 0.778155 0.795713 0.252091 0.745244 0.514644 0.699248 0.107066 0.705121 0.759360 0.729932 0.662827 0.673980 0.757395 0.177509 -0.999718 0.008160 0.515198 0.717405 0.749314 0.808297 0.798388 0.781501 0.827924 0.476250 0.477465 0.473560 0.602654 -0.644609 0.452885 0.640322 0.754714 -0.172540 0.354992 0.601055 0.819174 0.711585 0.644380 0.811865 0.809567 0.820840 0.810757 0.813480 0.763770 0.650897 0.194082 0.199098 0.618453 0.534376 0.243095 0.365170 -0.181111 0.811825 -0.050020 -0.767295 0.152134 0.795022 0.774773 NaN 0.462371 0.598497 NaN -0.137383 -0.124389 NaN -0.766012 NaN -0.116611 -0.000148 0.813480 -0.447094 -0.448563 0.732204 1.000000 0.736391 0.454959 0.819982 0.353661 0.354251 0.322984 -0.042696 0.000544 -0.300915 0.641714 -0.296690 0.547373 0.548010 -0.050853 -0.789712 0.781563 -0.312318 0.823029 0.620950 0.707710 0.746293 0.809923 0.825320 -0.633715
ROA -0.042308 0.521554 0.495835 0.475234 0.390649 0.366931 0.465279 0.421258 0.358429 0.434585 0.337427 0.305158 0.334727 0.436979 0.282390 0.303456 0.451710 0.331893 0.409057 0.424892 0.362631 0.238548 0.379153 0.274406 0.374542 0.209901 0.348500 0.314432 0.449874 0.308983 0.379095 0.365813 0.432549 -0.998156 0.299549 0.382330 0.352495 0.555692 0.506087 0.427528 0.421232 0.547484 0.490332 0.416216 0.457266 0.408269 -0.284034 0.368501 0.273738 0.408192 -0.089363 0.383614 0.343348 0.550019 0.488326 0.283651 0.542549 0.545224 0.546922 0.540313 0.543787 0.552789 0.387433 0.154157 0.176302 0.369859 0.430487 0.388079 0.295587 -0.085219 0.542453 -0.296360 -0.394672 0.111942 0.508753 0.399731 NaN 0.329950 0.319299 NaN -0.231989 -0.461979 NaN -0.399487 NaN 0.004362 0.001430 0.543787 -0.312066 -0.313317 0.222390 0.736391 1.000000 0.355422 0.535566 0.335363 0.500737 0.421160 0.272791 0.009977 -0.540925 0.115664 -0.195992 0.930664 0.930391 0.241576 -0.382784 0.530994 -0.614837 0.432289 0.354023 0.353912 0.465952 0.414927 0.409342 -0.934236
Dividend Yield -0.034417 0.509612 0.298163 0.446283 0.059834 0.588728 0.456491 0.734524 -0.014600 0.382291 0.174925 0.465298 0.116790 0.597521 0.748437 -0.025028 0.600168 0.379398 0.657587 0.589013 0.672055 0.282386 0.684401 0.585495 0.719022 0.517509 0.637939 0.467530 0.643803 0.642161 0.193904 0.725983 0.056191 NaN -0.002847 0.198212 0.346494 0.358063 0.495792 0.601261 0.560437 0.512870 0.072567 0.010598 0.042223 0.719348 -0.542459 0.676650 0.554704 0.598379 -0.579108 0.267755 0.367252 0.503022 0.580925 0.542067 0.461675 0.465754 0.512227 0.495046 0.464382 0.541265 0.238411 NaN 0.189181 0.176497 0.286560 0.084109 0.090003 -0.428400 0.461879 -0.104512 -0.379661 0.134710 0.411993 0.440024 NaN 0.541220 0.778007 NaN -0.357473 0.648131 NaN -0.467289 NaN 0.164460 0.106204 0.464382 -0.677294 -0.677477 0.407742 0.454959 0.355422 1.000000 0.507606 0.173191 0.119124 0.039246 -0.271151 0.318161 -0.164491 0.176530 -0.431179 0.273831 0.259521 -0.228697 -0.551744 0.401516 -0.291721 0.650252 0.776654 0.651511 0.631671 0.493907 0.473391 -0.367576
EBITDA 0.459507 0.893930 0.755620 0.774528 0.445262 0.794780 0.948209 0.811964 0.610363 0.928676 0.571173 0.514555 0.571138 0.789369 0.584368 0.292195 0.908397 0.819807 0.875104 0.911802 0.816401 0.384840 0.655862 0.479234 0.783742 0.322194 0.713992 0.715742 0.688751 0.666324 0.852597 0.745910 0.496826 -0.994126 0.355522 0.621864 0.691834 0.948290 0.976884 0.928043 0.910530 0.997020 0.689425 0.689485 0.687971 0.800227 -0.667037 0.638370 0.670760 0.890698 -0.223317 0.758662 0.825635 0.995909 0.861957 0.666533 0.989588 0.986592 0.995702 0.995502 0.989706 0.958710 0.707423 -0.518163 0.093204 0.725870 0.764928 0.540730 0.493078 -0.060593 0.989587 -0.121517 -0.898227 0.135136 0.895195 0.896639 NaN 0.685276 0.656999 NaN -0.174209 0.051397 NaN -0.902161 NaN -0.022731 -0.044253 0.989706 -0.616589 -0.616896 0.663687 0.819982 0.535566 0.507606 1.000000 0.453367 0.498717 0.515595 0.081854 -0.097719 -0.249215 0.565536 -0.422009 0.313364 0.323627 0.063819 -0.903257 0.934947 -0.200721 0.807124 0.625276 0.712247 0.631851 0.936925 0.931969 -0.433340
Adjusted Close 0.619985 0.444224 0.473965 0.504771 0.378606 0.193450 0.418537 0.119701 0.591956 0.638268 0.680694 0.315841 0.718175 0.081577 -0.187575 0.264886 0.427452 0.392655 0.345203 0.390790 0.139483 0.497480 -0.010858 0.020068 0.304657 0.536428 0.299716 0.385391 0.242296 0.075743 0.235667 0.123797 0.371561 -0.986644 0.169553 0.245007 0.286653 0.557023 0.335777 0.189452 0.140026 0.483794 0.498964 0.623821 0.583538 0.250136 -0.288286 0.046891 0.300075 0.438836 0.097046 0.484796 0.141911 0.479009 0.302796 0.288060 0.502071 0.505920 0.477633 0.447308 0.501551 0.472072 0.447033 -0.497031 -0.115937 0.354503 0.594478 0.580660 0.213421 0.054105 0.502165 -0.007043 -0.442683 -0.053395 0.264162 0.291215 NaN 0.601011 0.301034 NaN 0.086694 -0.412116 NaN -0.340221 NaN -0.051818 0.049496 0.501551 -0.084340 -0.083084 0.156640 0.353661 0.335363 0.173191 0.453367 1.000000 0.802313 0.684270 0.593548 -0.030914 0.219888 0.339022 -0.094758 0.263307 0.265742 0.248609 -0.217893 0.378378 -0.041161 0.102937 -0.086269 0.289037 0.295518 0.495920 0.480909 -0.127912
EPS 0.523601 0.530160 0.518473 0.566032 0.443999 0.073515 0.421750 0.226360 0.801115 0.683721 0.488403 0.109557 0.542015 0.198444 -0.121326 0.328370 0.370112 0.209601 0.246678 0.276776 0.078189 0.176858 -0.162700 0.018291 0.193856 0.201071 0.167023 0.134409 0.044722 0.019467 0.399038 0.056630 0.674720 -0.997707 0.526261 0.203398 0.196994 0.661444 0.436713 0.219269 0.223642 0.513949 0.710256 0.804282 0.770798 0.311755 -0.086300 0.162015 0.101276 0.403575 0.097356 0.532687 0.289497 0.522559 0.324257 0.085602 0.549130 0.546258 0.514060 0.502552 0.548535 0.570755 0.383020 -0.506499 -0.065295 0.335572 0.639429 0.807762 0.314444 0.271836 0.549147 -0.227752 -0.433468 0.000732 0.319236 0.355268 NaN 0.539185 0.057103 NaN 0.000194 -0.369792 NaN -0.420947 NaN -0.030393 -0.021077 0.548535 -0.204843 -0.203228 -0.026071 0.354251 0.500737 0.119124 0.498717 0.802313 1.000000 0.947481 0.854541 -0.081638 -0.197831 0.033858 -0.152459 0.379593 0.391987 0.445494 -0.233504 0.360883 -0.309169 0.023514 -0.157475 0.166355 0.259535 0.411061 0.383784 -0.267319
Revenue per Share 0.590446 0.575447 0.551699 0.608029 0.467818 0.093439 0.462106 0.262199 0.884384 0.732139 0.406675 0.026085 0.464509 0.267337 -0.085372 0.344741 0.370856 0.224334 0.266849 0.272135 0.104678 0.049887 -0.147204 0.051807 0.201764 0.058282 0.141442 0.146174 0.010094 0.038049 0.503559 0.067595 0.733727 0.999831 0.607443 0.212850 0.216755 0.703728 0.504135 0.280912 0.301914 0.520334 0.784664 0.898362 0.853122 0.333327 -0.066532 0.213466 0.084311 0.459711 0.083214 0.618489 0.379799 0.529840 0.366107 0.065854 0.548439 0.544444 0.520847 0.527159 0.547654 0.608141 0.421082 -0.595125 -0.065726 0.326136 0.679816 0.878862 0.294864 0.407727 0.548439 -0.226537 -0.471502 0.018434 0.394511 0.423522 NaN 0.439191 0.000023 NaN -0.122572 -0.299622 NaN -0.490204 NaN -0.010042 0.010112 0.547654 -0.276828 -0.275014 0.009454 0.322984 0.421160 0.039246 0.515595 0.684270 0.947481 1.000000 0.865281 -0.099988 -0.262055 0.032868 -0.265353 0.300441 0.314675 0.499811 -0.275461 0.410086 -0.305793 0.055641 -0.140054 0.143404 0.213366 0.442715 0.410186 -0.211814
Book Value per Share 0.386363 0.217919 0.264833 0.306903 0.341411 -0.335298 0.035306 -0.072300 0.703739 0.202361 0.333253 -0.089497 0.397991 -0.122376 -0.360214 0.279674 -0.034659 -0.193580 -0.170712 -0.160734 -0.325753 -0.105347 -0.531586 -0.230898 -0.200715 -0.025978 -0.304373 -0.418151 -0.353399 -0.336280 0.122798 -0.325563 0.656947 -0.989137 0.594914 -0.081884 -0.171275 0.312352 0.061279 -0.169410 -0.139616 0.089999 0.532506 0.642386 0.599335 -0.093260 0.289186 -0.081959 -0.266180 0.020823 0.172797 0.221797 0.006231 0.104630 -0.006783 -0.289923 0.127746 0.126164 0.093144 0.101013 0.126205 0.206356 0.084235 -0.719575 -0.163858 0.016674 0.396664 0.749641 0.128291 0.519829 0.127664 -0.280958 -0.032514 -0.045475 -0.083617 -0.043837 NaN -0.312143 -0.340845 NaN -0.051191 -0.283570 NaN -0.039619 NaN 0.034162 0.015719 0.126205 0.100955 0.102958 -0.417937 -0.042696 0.272791 -0.271151 0.081854 0.593548 0.854541 0.865281 1.000000 -0.055944 -0.171679 -0.312759 -0.011636 0.249329 0.256599 0.575427 0.176717 -0.030716 -0.329352 -0.376149 -0.516744 -0.302136 -0.127581 -0.002978 -0.037874 -0.075322
P/E Ratio -0.202693 -0.116059 -0.105042 -0.087545 -0.091058 -0.062558 -0.093285 -0.103840 -0.084247 -0.074726 -0.058784 -0.031267 -0.062788 -0.102781 0.063916 -0.078795 -0.079249 -0.032340 -0.073695 -0.071767 -0.062131 -0.029875 -0.119853 -0.064350 -0.069459 -0.032807 -0.067504 -0.103423 -0.075511 -0.058074 -0.077827 -0.063927 -0.120690 0.999587 -0.094276 -0.091146 -0.024883 -0.113940 -0.104909 -0.083529 -0.085608 -0.098661 -0.126953 -0.097318 -0.112572 -0.102570 0.038228 0.160180 -0.035225 -0.068307 0.012048 -0.282701 -0.071663 -0.101582 -0.096027 -0.039003 -0.098515 -0.099145 -0.100567 -0.102605 -0.099098 -0.114227 0.030729 -0.013485 -0.065713 -0.051277 -0.083234 -0.092861 -0.052486 -0.108176 -0.098465 0.063590 0.078770 -0.176582 0.242545 0.260862 NaN 0.525210 -0.052807 NaN 0.858022 -0.206225 NaN 0.100888 NaN -0.003426 0.078167 -0.099098 0.315127 0.314571 -0.072730 0.000544 0.009977 0.318161 -0.097719 -0.030914 -0.081638 -0.099988 -0.055944 1.000000 0.071260 -0.046076 -0.209572 0.053448 0.037398 -0.072187 0.070319 0.278229 -0.307089 0.166482 0.103161 -0.069557 0.267740 -0.062675 -0.055950 -0.019480
P/S Ratio 0.223491 -0.324591 -0.288216 -0.267715 -0.267222 -0.149271 -0.214688 -0.338157 -0.225170 -0.138799 0.062153 -0.016392 0.068012 -0.381742 -0.287170 -0.233662 -0.168087 0.006164 -0.151030 -0.116025 -0.181838 0.213312 -0.090191 -0.224131 -0.141084 0.114809 -0.131853 -0.005035 -0.031525 -0.173970 -0.262965 -0.186036 -0.414813 -0.990638 -0.408901 -0.212581 -0.065968 -0.294752 -0.316914 -0.258245 -0.297261 -0.242676 -0.365597 -0.239072 -0.298877 -0.315976 0.012973 -0.383165 0.001327 -0.146892 0.161611 -0.147560 -0.248153 -0.254768 -0.311585 -0.011877 -0.230840 -0.231036 -0.249302 -0.269233 -0.232382 -0.316586 -0.075088 0.610981 -0.250189 -0.104282 -0.187296 -0.271275 -0.173526 -0.148645 -0.230632 0.383316 0.106113 -0.141628 -0.104946 -0.155980 NaN 0.627939 -0.033426 NaN 0.259569 -0.322955 NaN 0.199400 NaN -0.048367 0.036655 -0.232382 0.445181 0.446049 -0.019853 -0.300915 -0.540925 -0.164491 -0.249215 0.219888 -0.197831 -0.262055 -0.171679 0.071260 1.000000 0.358575 0.388185 -0.487162 -0.498070 -0.291210 0.182550 -0.169434 0.361628 -0.158521 -0.275159 -0.144860 -0.194002 -0.093184 -0.080148 0.586275
P/B Ratio 0.483250 0.308822 0.259441 0.371152 -0.007296 0.688089 0.557089 0.229976 0.037356 0.562690 0.232148 0.172698 0.229352 0.391747 0.274859 -0.118137 0.467586 0.865894 0.611044 0.632265 0.670760 0.214213 0.653090 0.312626 0.530848 0.007390 0.578459 0.766027 0.573900 0.499965 0.522671 0.606311 -0.260289 -0.932956 -0.382016 0.294142 0.646548 0.450879 0.545734 0.607673 0.573125 0.568972 0.118616 0.250069 0.178370 0.320135 -0.609468 0.158780 0.613202 0.651932 -0.022470 0.315488 0.429477 0.551304 0.443089 0.610350 0.555822 0.561559 0.555185 0.542003 0.555648 0.446489 0.495978 0.943827 -0.018871 0.497770 0.286535 -0.076299 0.130260 -0.139151 0.555906 0.350930 -0.677532 0.086825 0.632241 0.632261 NaN 0.516069 0.480775 NaN 0.025577 -0.163740 NaN -0.628156 NaN -0.182648 0.015816 0.555648 -0.234865 -0.235144 0.846290 0.641714 0.115664 0.176530 0.565536 0.339022 0.033858 0.032868 -0.312759 -0.046076 0.358575 1.000000 -0.141618 0.003764 0.010735 -0.345636 -0.660326 0.566779 0.161495 0.672518 0.419103 0.569714 0.401892 0.718953 0.752767 -0.051922
SalesGrowth -0.292571 -0.572309 -0.585901 -0.409876 -0.492418 -0.482406 -0.548718 -0.387436 -0.344250 -0.531659 -0.325488 -0.321821 -0.320837 -0.517043 -0.190356 -0.428576 -0.475378 -0.369892 -0.560490 -0.482464 -0.380782 -0.301597 -0.439440 -0.347100 -0.552395 -0.264261 -0.468194 -0.358682 -0.385252 -0.376168 -0.352298 -0.399893 -0.299290 -0.976494 -0.115904 -0.577561 -0.486392 -0.500928 -0.469781 -0.404713 -0.397018 -0.421188 -0.537080 -0.457127 -0.514154 -0.522840 0.475974 -0.509904 -0.482571 -0.418951 0.279729 -0.525920 -0.345581 -0.416315 -0.401820 -0.474480 -0.396249 -0.406986 -0.424229 -0.435704 -0.402936 -0.487480 -0.384475 0.280786 -0.332239 -0.078229 -0.518822 -0.345445 0.047776 0.182819 -0.396208 0.050943 0.407769 0.065902 -0.357588 -0.373902 NaN -0.381350 -0.552927 NaN -0.168692 -0.312941 NaN 0.434179 NaN -0.070339 0.062651 -0.402936 0.596517 0.597114 -0.427525 -0.296690 -0.195992 -0.431179 -0.422009 -0.094758 -0.152459 -0.265353 -0.011636 -0.209572 0.388185 -0.141618 1.000000 -0.152297 -0.176897 -0.284515 0.322324 -0.572484 -0.299480 -0.404356 -0.414742 -0.474269 -0.441327 -0.506315 -0.483163 0.280133
OperatingProfitMargin -0.054517 0.356645 0.368910 0.301516 0.340783 0.203771 0.281743 0.255578 0.251070 0.259172 0.314110 0.293320 0.308519 0.257388 0.160492 0.294791 0.279520 0.152628 0.248751 0.242990 0.169853 0.275210 0.051480 0.158800 0.241709 0.206264 0.194497 0.143278 0.329490 0.165444 0.182498 0.187868 0.339590 -0.998504 0.224370 0.280804 0.212570 0.350094 0.284288 0.215348 0.207061 0.325019 0.348906 0.277981 0.321182 0.263829 -0.184571 0.235837 0.179762 0.201749 -0.062140 -0.132898 0.166657 0.327102 0.311717 0.184340 0.316744 0.319972 0.325980 0.320785 0.318532 0.341229 0.253235 -0.030739 0.165182 0.202915 0.312597 0.292376 0.177346 -0.186259 0.316655 -0.247523 -0.202522 -0.071403 0.171348 0.201929 NaN 0.274057 0.222964 NaN -0.270370 -0.513193 NaN -0.198764 NaN 0.029021 0.189331 0.318532 -0.154607 -0.155729 0.100476 0.547373 0.930664 0.273831 0.313364 0.263307 0.379593 0.300441 0.249329 0.053448 -0.487162 0.003764 -0.152297 1.000000 0.997876 0.263952 -0.162645 0.337657 -0.547537 0.191728 0.152999 0.198330 0.277293 0.229346 0.218378 -0.953429
netProfitMargin -0.026086 0.368798 0.380704 0.316172 0.349220 0.207253 0.294362 0.262041 0.269678 0.273949 0.311968 0.279936 0.308577 0.270078 0.159774 0.300479 0.287034 0.159744 0.255052 0.254416 0.175168 0.290952 0.088194 0.156056 0.244298 0.202800 0.198497 0.155138 0.329195 0.169494 0.201991 0.192292 0.353990 -0.997865 0.240197 0.286818 0.211376 0.363301 0.297571 0.225861 0.218954 0.334519 0.363626 0.295056 0.336563 0.274255 -0.186392 0.247161 0.182013 0.213795 -0.052715 0.130640 0.180486 0.338009 0.304110 0.186262 0.331697 0.335034 0.336754 0.332069 0.333263 0.352820 0.258242 -0.108167 0.156955 0.210166 0.327282 0.309349 0.183647 -0.011010 0.331598 -0.245683 -0.215548 -0.057541 0.218932 0.210482 NaN 0.343075 0.219970 NaN -0.240221 -0.535993 NaN -0.213568 NaN 0.031234 -0.050409 0.333263 -0.177582 -0.178597 0.109417 0.548010 0.930391 0.259521 0.323627 0.265742 0.391987 0.314675 0.256599 0.037398 -0.498070 0.010735 -0.176897 0.997876 1.000000 0.268178 -0.173556 0.379747 -0.529741 0.210759 0.163945 0.201856 0.261694 0.238596 0.227051 -0.953684
NetWorkingCapital 0.169821 0.384305 0.626416 0.268602 0.840850 -0.096348 0.173569 -0.010627 0.586144 0.233810 0.534774 0.321786 0.558075 0.075944 -0.460940 0.824682 0.045535 -0.197363 0.033360 -0.066615 -0.327624 0.110560 -0.437929 -0.264161 0.028602 0.226216 -0.095171 -0.272694 -0.192152 -0.197757 0.140507 -0.297532 0.696560 -0.996811 0.561369 0.437230 -0.018994 0.301917 0.092397 -0.086428 -0.079744 0.059216 0.653448 0.533230 0.611690 0.139623 -0.035069 0.150852 0.048316 -0.096394 0.258907 0.294222 0.084964 0.087324 0.066942 0.034365 0.082644 0.096819 0.088156 0.110711 0.088753 0.178040 0.145932 -0.460261 0.180251 -0.031700 0.514825 0.596180 0.021588 0.452269 0.082406 -0.295301 -0.009520 -0.442956 -0.177699 -0.123761 NaN -0.243944 -0.043371 NaN -0.058793 0.040116 NaN 0.024794 NaN 0.137697 0.046829 0.088753 -0.116532 -0.117086 -0.281610 -0.050853 0.241576 -0.228697 0.063819 0.248609 0.445494 0.499811 0.575427 -0.072187 -0.291210 -0.345636 -0.284515 0.263952 0.268178 1.000000 0.320516 0.136964 0.060755 -0.352445 -0.351885 -0.113085 0.039455 0.002750 -0.044456 -0.211252
NetWorkingCapital/Sales -0.352709 -0.698806 -0.466024 -0.648861 -0.083956 -0.808813 -0.829363 -0.783325 -0.338429 -0.787381 -0.166754 -0.254668 -0.152507 -0.786215 -0.765649 0.056890 -0.811595 -0.856190 -0.821129 -0.874885 -0.935294 -0.204592 -0.781290 -0.586783 -0.734907 -0.079933 -0.725145 -0.755443 -0.710001 -0.751446 -0.804841 -0.861928 -0.195497 -0.998670 -0.140647 -0.391310 -0.653922 -0.764139 -0.913576 -0.948543 -0.945293 -0.896415 -0.390186 -0.443514 -0.405425 -0.743091 0.624605 -0.635952 -0.626715 -0.912695 0.321370 -0.567716 -0.776115 -0.887082 -0.777734 -0.624433 -0.881496 -0.874672 -0.887045 -0.888241 -0.879281 -0.832004 -0.614390 0.613093 -0.028563 -0.672550 -0.512977 -0.266307 -0.425723 0.154528 -0.881579 -0.016032 0.850507 -0.233693 -0.892548 -0.894903 NaN -0.546045 -0.596689 NaN 0.196407 -0.104275 NaN 0.895564 NaN 0.062286 0.207529 -0.879281 0.561819 0.561992 -0.764049 -0.789712 -0.382784 -0.551744 -0.903257 -0.217893 -0.233504 -0.275461 0.176717 0.070319 0.182550 -0.660326 0.322324 -0.162645 -0.173556 0.320516 1.000000 -0.817084 0.234233 -0.922087 -0.753674 -0.731813 -0.583845 -0.881840 -0.893349 0.321793
avgReceivables 0.482942 0.921047 0.847208 0.752960 0.553345 0.836302 0.994369 0.711364 0.592216 0.977365 0.695159 0.600529 0.698446 0.819542 0.445668 0.416937 0.903008 0.834468 0.921502 0.936298 0.777745 0.464672 0.695024 0.443527 0.822281 0.380217 0.766439 0.761262 0.727467 0.680187 0.835601 0.720536 0.447152 0.936484 0.264632 0.762605 0.738259 0.924671 0.936973 0.879867 0.857667 0.930706 0.723647 0.696195 0.714853 0.850233 -0.784109 0.706620 0.785873 0.870419 -0.108016 0.745099 0.782892 0.932130 0.778388 0.783665 0.928301 0.929241 0.937629 0.942878 0.929995 0.902652 0.802054 -0.805370 0.128755 0.628505 0.839608 0.502937 0.367753 -0.087196 0.928291 0.042201 -0.907463 0.004242 0.873947 0.876040 NaN 0.759887 0.716712 NaN 0.269499 0.082538 NaN -0.878891 NaN 0.020009 -0.142094 0.929995 -0.615298 -0.616201 0.687042 0.781563 0.530994 0.401516 0.934947 0.378378 0.360883 0.410086 -0.030716 0.278229 -0.169434 0.566779 -0.572484 0.337657 0.379747 0.136964 -0.817084 1.000000 0.042688 0.787713 0.609630 0.758659 0.716439 0.954764 0.942367 -0.546460
DebtorDays 0.335574 -0.095922 0.065373 -0.265706 0.160295 0.059706 0.022533 -0.289130 -0.130206 0.015507 0.253995 0.196750 0.256462 -0.129469 -0.419598 0.248336 -0.021829 -0.001831 0.055905 0.028605 -0.171141 0.383176 0.026306 -0.136371 0.068391 0.456455 0.031550 0.083272 -0.089020 -0.111189 -0.192688 -0.153389 -0.259242 0.832725 -0.382419 0.329990 0.146017 -0.153489 -0.225136 -0.218439 -0.259080 -0.198902 -0.029449 -0.091465 -0.040983 -0.088586 -0.213662 -0.140609 0.228111 -0.228572 0.155550 0.172581 -0.174555 -0.202967 -0.253345 0.214519 -0.186384 -0.184691 -0.190127 -0.200264 -0.183270 -0.238452 -0.066466 0.194526 0.197860 -0.152962 0.047502 -0.193078 -0.197228 -0.167708 -0.186349 0.356271 0.030690 -0.194296 -0.147411 -0.180577 NaN 0.337595 0.239866 NaN 0.479923 0.165485 NaN 0.131327 NaN 0.008937 -0.113304 -0.183270 -0.069906 -0.069935 0.176954 -0.312318 -0.614837 -0.291721 -0.200721 -0.041161 -0.309169 -0.305793 -0.329352 -0.307089 0.361628 0.161495 -0.299480 -0.547537 -0.529741 0.060755 0.234233 0.042688 1.000000 -0.150085 -0.133599 0.012290 -0.230638 -0.020322 -0.024298 0.535998
AvgPayables 0.219959 0.646040 0.446181 0.666544 0.059528 0.879892 0.782791 0.717178 0.112368 0.717430 0.096495 0.363634 0.043089 0.836979 0.809553 -0.083743 0.751865 0.879553 0.879211 0.862322 0.996201 0.186012 0.913803 0.666027 0.837477 0.055834 0.864238 0.859936 0.854811 0.869421 0.678382 0.964779 -0.016492 0.792631 -0.074794 0.369626 0.619275 0.632352 0.837049 0.924771 0.913797 0.801964 0.220387 0.258965 0.225189 0.855031 -0.778916 0.705996 0.778501 0.840399 -0.371210 0.456861 0.686539 0.792321 0.748914 0.778793 0.770544 0.772459 0.799640 0.793556 0.770489 0.725829 0.639064 -0.871711 0.065494 0.515351 0.458937 0.055960 0.244206 -0.264279 0.770576 0.165221 -0.790539 0.066815 0.823257 0.825902 NaN 0.530249 0.702300 NaN -0.167147 0.179369 NaN -0.827725 NaN 0.056960 -0.163391 0.770489 -0.553101 -0.554108 0.838008 0.823029 0.432289 0.650252 0.807124 0.102937 0.023514 0.055641 -0.376149 0.166482 -0.158521 0.672518 -0.404356 0.191728 0.210759 -0.352445 -0.922087 0.787713 -0.150085 1.000000 0.889736 0.870390 0.737334 0.861964 0.870793 -0.530278
CreditorDays -0.057388 0.549122 0.354440 0.525144 0.042868 0.781859 0.604378 0.711749 -0.057098 0.520780 -0.000026 0.372077 -0.069049 0.751630 0.832129 -0.060601 0.667694 0.650948 0.785805 0.747549 0.889902 0.251787 0.905103 0.713645 0.801877 0.260368 0.855128 0.766274 0.862000 0.865472 0.423885 0.883190 -0.067294 0.744392 -0.094542 0.335257 0.454686 0.434222 0.656436 0.785162 0.762030 0.623892 0.078174 0.028533 0.043099 0.868891 -0.731506 0.749039 0.704478 0.710880 -0.460608 0.466263 0.513227 0.614024 0.651010 0.731317 0.579252 0.585578 0.624489 0.610686 0.580905 0.572103 0.490453 -0.981885 0.184268 0.345230 0.298106 -0.062933 0.152716 -0.420068 0.579331 0.063522 -0.552587 0.029164 0.617528 0.620779 NaN 0.562823 0.736772 NaN -0.181337 0.363163 NaN -0.603076 NaN 0.139320 -0.135230 0.580905 -0.674624 -0.676034 0.681171 0.620950 0.354023 0.776654 0.625276 -0.086269 -0.157475 -0.140054 -0.516744 0.103161 -0.275159 0.419103 -0.414742 0.152999 0.163945 -0.351885 -0.753674 0.609630 -0.133599 0.889736 1.000000 0.867230 0.724929 0.657594 0.658279 -0.587229
totalDebt 0.322557 0.701198 0.590457 0.634922 0.304671 0.871843 0.761685 0.613433 0.152722 0.744249 0.444327 0.599004 0.399062 0.838379 0.658500 0.192558 0.746889 0.777415 0.946521 0.841053 0.870833 0.344706 0.920729 0.719021 0.970286 0.280154 0.997660 0.850847 0.994241 0.950603 0.537318 0.885533 0.021437 0.999116 -0.113558 0.468724 0.653192 0.600535 0.732208 0.798280 0.773908 0.714454 0.305713 0.290032 0.296389 0.907590 -0.934729 0.701062 0.934762 0.758041 -0.295774 0.575749 0.554502 0.705186 0.638247 0.934666 0.687622 0.692774 0.720737 0.701954 0.693480 0.653909 0.662266 0.121639 0.246972 0.462462 0.608916 0.140039 0.195835 -0.345313 0.687736 0.130984 -0.730966 -0.059194 0.738909 0.744367 NaN 0.719493 0.827259 NaN -0.269471 0.150722 NaN -0.757579 NaN 0.062334 -0.001811 0.693480 -0.569801 -0.570985 0.811078 0.707710 0.353912 0.651511 0.712247 0.289037 0.166355 0.143404 -0.302136 -0.069557 -0.144860 0.569714 -0.474269 0.198330 0.201856 -0.113085 -0.731813 0.758659 0.012290 0.870390 0.867230 1.000000 0.812175 0.827105 0.810223 -0.351212
debtRatioToCapital -0.008602 0.633108 0.585365 0.554440 0.377986 0.752837 0.661336 0.502481 0.170774 0.630927 0.405336 0.544921 0.367208 0.702377 0.548967 0.280584 0.637893 0.645975 0.799458 0.700939 0.705018 0.317440 0.835740 0.639251 0.816617 0.223002 0.804836 0.724722 0.804964 0.738646 0.443250 0.727395 0.096888 -0.860222 -0.077352 0.507963 0.639511 0.578459 0.640065 0.659097 0.634411 0.639096 0.380514 0.329519 0.361877 0.692416 -0.760823 0.578690 0.760928 0.598950 -0.281261 0.364632 0.453293 0.629989 0.596119 0.759782 0.606711 0.614170 0.641385 0.624276 0.613614 0.615728 0.605400 0.171486 0.352433 0.384888 0.548042 0.182124 0.165666 -0.469745 0.606774 -0.015931 -0.605215 -0.028864 0.663583 0.668440 NaN 0.697632 0.725539 NaN 0.131316 0.022113 NaN -0.623278 NaN 0.016544 0.083630 0.613614 -0.386245 -0.388302 0.567448 0.746293 0.465952 0.631671 0.631851 0.295518 0.259535 0.213366 -0.127581 0.267740 -0.194002 0.401892 -0.441327 0.277293 0.261694 0.039455 -0.583845 0.716439 -0.230638 0.737334 0.724929 0.812175 1.000000 0.703608 0.692212 -0.397800
CummulativeCashflowFromOperations 0.571003 0.846114 0.738138 0.770253 0.419053 0.869189 0.947662 0.690847 0.529690 0.947629 0.726763 0.626308 0.726723 0.785369 0.517107 0.265333 0.884799 0.932000 0.937687 0.942459 0.858420 0.423622 0.762726 0.538351 0.857163 0.314407 0.830095 0.833484 0.805407 0.740757 0.809162 0.800781 0.318187 0.800476 0.138845 0.614226 0.763457 0.889749 0.928152 0.900952 0.874628 0.938327 0.610982 0.665737 0.642289 0.821380 -0.835489 0.664068 0.836165 0.926919 -0.206320 0.730860 0.742887 0.930859 0.794069 0.835227 0.926130 0.928162 0.935931 0.931068 0.927707 0.888605 0.773847 -0.596373 0.113988 0.654706 0.774465 0.453250 0.344481 -0.118732 0.926205 0.074898 -0.928690 0.061804 0.901112 0.904737 NaN 0.757298 0.736271 NaN -0.134956 0.015879 NaN -0.911074 NaN 0.001368 -0.039499 0.927707 -0.561970 -0.562360 0.798775 0.809923 0.414927 0.493907 0.936925 0.495920 0.411061 0.442715 -0.002978 -0.062675 -0.093184 0.718953 -0.506315 0.229346 0.238596 0.002750 -0.881840 0.954764 -0.020322 0.861964 0.657594 0.827105 0.703608 1.000000 0.996563 -0.328408
CummulativeCNetProfits 0.549695 0.812154 0.702548 0.748444 0.375667 0.876469 0.935087 0.667879 0.490601 0.929165 0.733121 0.641407 0.732399 0.766615 0.509996 0.221967 0.869284 0.953123 0.922900 0.937900 0.867654 0.409308 0.760828 0.528133 0.834946 0.284794 0.813330 0.834663 0.789419 0.724515 0.806896 0.805411 0.273339 -0.858983 0.097075 0.602895 0.771767 0.874286 0.919984 0.899318 0.872669 0.934020 0.580017 0.638740 0.612069 0.795514 -0.828531 0.634509 0.829813 0.920105 -0.195712 0.682360 0.734147 0.924851 0.788262 0.828291 0.920581 0.922408 0.929241 0.923176 0.921874 0.870004 0.762143 -0.610877 0.110338 0.659436 0.732232 0.406500 0.338917 -0.133461 0.920646 0.097129 -0.927470 0.066422 0.895601 0.899353 NaN 0.723516 0.725793 NaN -0.120915 -0.033467 NaN -0.905269 NaN -0.012850 -0.049815 0.921874 -0.548343 -0.548804 0.816261 0.825320 0.409342 0.473391 0.931969 0.480909 0.383784 0.410186 -0.037874 -0.055950 -0.080148 0.752767 -0.483163 0.218378 0.227051 -0.044456 -0.893349 0.942367 -0.024298 0.870793 0.658279 0.810223 0.692212 0.996563 1.000000 -0.319169
Innovation % 0.133758 -0.465968 -0.441973 -0.372228 -0.366640 -0.363416 -0.397697 -0.435961 -0.221678 -0.344192 -0.248755 -0.328557 -0.227889 -0.442395 -0.329281 -0.310360 -0.403912 -0.250997 -0.389036 -0.382282 -0.347260 -0.268106 -0.623193 -0.289076 -0.375828 -0.219074 -0.346285 -0.276069 -0.572613 -0.335041 -0.303994 -0.355454 -0.354171 0.861291 -0.265766 -0.371524 -0.278767 -0.421514 -0.428955 -0.400964 -0.393780 -0.438958 -0.362920 -0.244700 -0.307161 -0.423555 0.302082 -0.408488 -0.285385 -0.325193 0.139299 -0.382873 -0.307256 -0.442633 -0.449911 -0.301778 -0.422438 -0.427174 -0.442578 -0.442891 -0.424620 -0.450437 -0.315276 -0.658010 -0.221992 -0.284574 -0.338684 -0.253384 -0.229687 0.250323 -0.422338 0.284210 0.291883 -0.143250 -0.459862 -0.324436 NaN -0.353359 -0.344214 NaN 0.457471 -0.286544 NaN 0.310840 NaN -0.035138 -0.032575 -0.424620 0.339453 0.341055 -0.216684 -0.633715 -0.934236 -0.367576 -0.433340 -0.127912 -0.267319 -0.211814 -0.075322 -0.019480 0.586275 -0.051922 0.280133 -0.953429 -0.953684 -0.211252 0.321793 -0.546460 0.535998 -0.530278 -0.587229 -0.351212 -0.397800 -0.328408 -0.319169 1.000000
In [ ]:
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns

# Define a color palette to cover all columns
color_palette = sns.color_palette("husl", len(numeric_columns))

# Iterate through numeric columns in batches for better visualization
for i in range(0, len(numeric_columns), 10):
    # Select the current batch of columns
    batch_data = df[numeric_columns[i:i+10]].replace([np.inf, -np.inf], np.nan)
    batch_columns = batch_data.columns
    num_plots = len(batch_columns)

    # Calculate the layout for subplots based on the number of columns in the batch
    fig, axes = plt.subplots(nrows=(num_plots // 5) + (num_plots % 5 > 0), ncols=5, figsize=(15, 10))
    axes = axes.flatten()  # Flatten to easily iterate over axes

    # Plot each column in the batch with a specific color
    for j, column in enumerate(batch_columns):
        batch_data[column].hist(ax=axes[j], bins=20, color=color_palette[i + j % len(color_palette)])
        axes[j].set_title(column)

    # Hide any unused axes in the current batch
    for k in range(j + 1, len(axes)):
        axes[k].set_visible(False)

    plt.tight_layout()
    plt.show()

User Story 1: Stacked Bar Chart to understand the Asset / Liability & Net Liquid Funds in the Org¶

How is the Company growing?

Does it have more Liability than Assets? If the company has less Liability, are they able to pay off their liability without hassle?

How much liquidation does the company have?

Whats Expected:

  • We expect the Company to have more liquidity to ensure that the company is stable
  • we expect the companies liability to be way less than the assets.

Plotting the values of Current Assets, Fixed Assets, and Intangible Assets over time

Columns used

  1. totalCurrentAssets (for Current Assets)
  2. totalNonCurrentAssets (for Fixed Assets)
  3. intangibleAssets (for Intangible Assets)
  4. year or fiscalDateEnding_balance (for Time/Years)
  5. Company column to differentiate every unique values in the company
In [ ]:
import pandas as pd
import matplotlib.pyplot as plt

# Check if 'year' column exists, and rename it if necessary
if 'year' not in df.columns:
    if 'fiscalDateEnding_balance' in df.columns:
        # Extract year from 'fiscalDateEnding_balance' if it exists
        df['year'] = pd.to_datetime(df['fiscalDateEnding_balance']).dt.year
    else:
        # Handle the case where no suitable year column is found
        raise ValueError("No 'year' or suitable year-related column found in DataFrame.")

# Get the unique list of companies
companies = df['Company'].unique()

# Loop through each company and generate a separate stacked bar chart
for company in companies:
    # Filter data for the current company
    company_data = df[df['Company'] == company]

    # Plot a stacked bar chart for the company
    plt.figure(figsize=(10, 6))

    # Plot stacked bars for each asset category
    plt.bar(company_data['year'], company_data['totalCurrentAssets'], label='Current Assets')
    plt.bar(company_data['year'], company_data['totalNonCurrentAssets'],
            bottom=company_data['totalCurrentAssets'], label='Fixed Assets')
    plt.bar(company_data['year'], company_data['intangibleAssets'],
            bottom=company_data['totalCurrentAssets'] + company_data['totalNonCurrentAssets'],
            label='Intangible Assets')

    # Adding labels, title, and legend
    plt.xlabel('Time (Years)')
    plt.ylabel('Values')
    plt.title(f'Asset Allocation for {company} Over Time')
    plt.legend()

    # Show the plot
    plt.tight_layout()
    plt.show()

Some Information to know

  • Fixed Asset: These are long-term investments (like property, machinery, and equipment) that contribute to long-term growth. When analyzing asset structure changes, an increase in fixed assets could indicate the company is focusing on expanding its operations or investing in infrastructure for future growth..

  • Current Asset: These are short-term assets (like cash, inventory, or receivables) that are easily converted into cash. If there's an increase in current assets, it suggests the company is focusing on maintaining liquidity and short-term financial stability. Those that we expect to convert to cash in one year.

  • Intangible Asset: These non-physical assets (like patents, trademarks, and goodwill) contribute to long-term value but dont directly affect liquidity. Changes in intangible assets might indicate investments in intellectual property or branding, which can support long-term growth.

Intrepretation

Analyzing asset structure changes to identify investments in liquidity or long-term growth opportunities.

  • The statement means examining how a company's assets have shifted over time to understand if they are investing more in liquid assets (short-term resources like cash) or in assets that will contribute to long-term growth (such as property, equipment, or research). This helps assess the company's focus on immediate financial stability versus future expansion

Analyzing the liability

In [ ]:
# Check if 'year' column exists, and rename it if necessary
if 'year' not in df.columns:
    if 'fiscalDateEnding_balance' in df.columns:
        # Extract year from 'fiscalDateEnding_balance' if it exists
        df['year'] = pd.to_datetime(df['fiscalDateEnding_balance']).dt.year
    else:
        # Handle the case where no suitable year column is found
        raise ValueError("No 'year' or suitable year-related column found in DataFrame.")

# Get the unique list of companies
companies = df['Company'].unique()

# Loop through each company and generate a separate plot for Total Liabilities
for company in companies:
    # Filter data for the current company
    company_data = df[df['Company'] == company]

    # Plot the Total Liabilities over the years for the current company
    plt.figure(figsize=(10, 6))

    # Plot Total Liabilities
    plt.plot(company_data['year'], company_data['totalLiabilities'], marker='o', label=f'Total Liabilities - {company}', color='b')

    # Adding labels, title, and legend
    plt.xlabel('Time (Years)')
    plt.ylabel('Total Liabilities')
    plt.title(f'Total Liabilities for {company} Over Time')
    plt.legend()

    # Show the plot
    plt.tight_layout()
    plt.show()

Overlaying the liability over the Assets

In [ ]:
import pandas as pd
import matplotlib.pyplot as plt

# Check if 'year' column exists, and rename it if necessary
if 'year' not in df.columns:
    if 'fiscalDateEnding_balance' in df.columns:
        # Extract year from 'fiscalDateEnding_balance' if it exists
        df['year'] = pd.to_datetime(df['fiscalDateEnding_balance']).dt.year
    else:
        # Handle the case where no suitable year column is found
        raise ValueError("No 'year' or suitable year-related column found in DataFrame.")

# Get the unique list of companies
companies = df['Company'].unique()

# Loop through each company and generate a combined plot for Asset and Liability growth
for company in companies:
    # Filter data for the current company
    company_data = df[df['Company'] == company]

    # Create the figure for the plot
    plt.figure(figsize=(12, 8))

    # Plot stacked bars for Asset Allocation
    plt.bar(company_data['year'], company_data['totalCurrentAssets'], label='Current Assets')
    plt.bar(company_data['year'], company_data['totalNonCurrentAssets'],
            bottom=company_data['totalCurrentAssets'], label='Fixed Assets')
    plt.bar(company_data['year'], company_data['intangibleAssets'],
            bottom=company_data['totalCurrentAssets'] + company_data['totalNonCurrentAssets'],
            label='Intangible Assets')

    # Plot Total Liabilities as a line chart
    plt.plot(company_data['year'], company_data['totalLiabilities'], marker='o',
             label=f'Total Liabilities - {company}', color='b', linestyle='-', linewidth=2)

    # Adding labels, title, and legend
    plt.xlabel('Time (Years)')
    plt.ylabel('Values')
    plt.title(f'Asset and Liability Growth for {company} Over Time')
    plt.legend()

    # Show the plot
    plt.tight_layout()
    plt.show()

Understanding the relationship between the Asset and the liabitliy - Intrepretation

Fill it here for each of the company

  1. List item
  2. List item

Understanding the Liquidation of the company using a Single Chart

Understanding the Asset & Liability using the chart is easy with ratios.

  • Quick ratio and current ratio will tell this more effectively. For Example
  1. Current Ratio This parameter is going to tell us how much asset we have including inventory we have to convert as a cash within a year vs total liability we have. If the value is strong it means that the company is focussed more towards selling its inventory.

Example: If a company has $200,000 in current assets and $150,000 in current liabilities, the current ratio is 1.33, meaning it has $1.33 in assets for every $1 in liabilities.

Current Ratio is Asset / Liability

  1. Quick Ratio

This ensures that we know the reality of the company. its the asset subracting the inventory we have. Even if the sales do not happen,we can answer how much of liquidy can the company have to pay off the loans?

Quick Ratio is (Asset-Inventory)/Liability

In [ ]:
# Get the unique list of companies
companies = df['Company'].unique()

# Loop through each company
for company in companies:
    # Filter data for the current company
    company_data = df[df['Company'] == company]

    # Create the figure and axes
    plt.figure(figsize=(10, 6))

    # Check if 'quickRatio' column exists, otherwise try a similar name or print available columns.
    if 'Quick Ratio' in company_data.columns:
        quick_ratio_column = 'Quick Ratio'
    elif 'Quick Ratio' in company_data.columns:  # Check for a possible alternative name
        quick_ratio_column = 'Quick Ratio'
    else:
        print(f"Column 'quickRatio' not found for {company}. Available columns: {company_data.columns}")
        continue  # Skip to the next company if the column is not found

    # Plot quick ratio using the identified column name
    plt.plot(company_data['year'], company_data[quick_ratio_column], marker='o', label='Quick Ratio')

    # Plot current ratio
    # Similar check can be implemented for 'currentRatio' if needed
    if 'Current Ratio' in company_data.columns:
        current_ratio_column = 'Current Ratio'
    elif 'Current Ratio' in company_data.columns:
        current_ratio_column = 'Current Ratio'
    else:
        print(f"Column 'currentRatio' not found for {company}. Available columns: {company_data.columns}")
        continue

    plt.plot(company_data['year'], company_data[current_ratio_column], marker='x', label='Current Ratio')
    # Add threshold lines
    plt.axhline(1, color='red', linestyle='--', label='Quick Ratio Threshold >(1.0)')

    # Customize the plot
    plt.xlabel('Year')
    plt.ylabel('Ratio')
    plt.title(f'Quick Ratio and Current Ratio for {company}')
    plt.legend()
    plt.grid(True)

    # Show the plot
    plt.show()

Liabilities grow faster than equity, the company is taking on more debt, which could increase financial risk. Stable or increasing equity suggests strong shareholder confidence.

User Story 2 : Liability Vs Equity¶

What to check?

  1. What is the ability of the company to payoff the debt?
  2. how much of the company is financed by debt (liabilities) versus owner's investment (equity)
  • A higher proportion of liabilities may indicate greater financial risk, while a higher equity proportion suggests stronger reliance on internal financing.

  • If liabilities are increasing significantly over time, it might signal potential over-leveraging, leading to liquidity risks.

  • Helps decide whether to reduce debt to maintain financial health.

  • A balanced or growing equity portion indicates a companys ability to fund itself without heavy borrowing, suggesting sustainability. It helps decide if the company can fund future growth without taking on excessive debt.

  • Investors can assess whether the companys reliance on debt versus equity aligns with their risk appetite. An increasing equity portion can make the company more attractive to investors looking for stability.

  • By observing trends, management can decide on financing strategies, such as issuing more equity, retaining earnings, or borrowing.

Required Columns

  1. totalLiabilities: Represents the total obligations of the company (debts, payables, etc.).
  2. totalShareholderEquity: Represents the equity portion, which includes retained earnings and the value contributed by shareholders.
  3. year: To represent the time axis.
  4. Company: To differentiate between companies if plotting for multiple companies.
In [ ]:
# Group data by year and company
grouped = df.groupby(['year', 'Company']).sum().reset_index()

# Get the unique companies
companies = grouped['Company'].unique()

# Create separate plots for each company
for company in companies:
    company_data = grouped[grouped['Company'] == company]

    plt.figure(figsize=(8, 6))
    plt.bar(company_data['year'], company_data['totalLiabilities'], label='Liabilities')
    plt.bar(company_data['year'], company_data['totalShareholderEquity'],
            bottom=company_data['totalLiabilities'], label='Equity')

    # Chart settings
    plt.title(f'Liabilities vs Equity (Year-wise) for {company}')
    plt.xlabel('Year')
    plt.ylabel('Value')
    plt.xticks(company_data['year'].unique())
    plt.legend()
    plt.tight_layout()
    plt.show()

Debt to Equity Ratio

Debt-to-Equity Ratio (D/E)= Total Liabilities / Total Shareholder Equity

  • Low D/E Ratio: Indicates that the company is primarily financed by equity rather than debt. It suggests lower financial risk.

  • High D/E Ratio: Indicates that the company relies heavily on debt to finance its operations, which could imply higher financial risk.

In [ ]:
df['D']
Out[ ]:
Index(['year', 'fiscalDateEnding_balance', 'reportedCurrency_balance',
       'totalAssets', 'totalCurrentAssets',
       'cashAndCashEquivalentsAtCarryingValue', 'cashAndShortTermInvestments',
       'inventory', 'currentNetReceivables', 'totalNonCurrentAssets',
       ...
       'NetWorkingCapital/Sales', 'avgReceivables', 'DebtorDays',
       'AvgPayables', 'CreditorDays', 'totalDebt', 'debtRatioToCapital',
       'CummulativeCashflowFromOperations', 'CummulativeCNetProfits',
       'Innovation %'],
      dtype='object', length=123)
In [ ]:
# Get the unique companies
companies = df['Company'].unique()

# Create a line plot for each company
for company in companies:
    company_data = df[df['Company'] == company]

    plt.figure(figsize=(8, 6))
    plt.plot(company_data['year'], company_data['Debt Equity Ratio'], marker='o', label=f'{company} D/E Ratio')

    # Chart settings
    plt.title(f'Debt-to-Equity Ratio Over Time for {company}')
    plt.xlabel('Year')
    plt.ylabel('Debt-to-Equity Ratio')
    plt.xticks(company_data['year'].unique())
    plt.axhline(1, color='red', linestyle='--', label='Threshold <(1)')  # Optional threshold line
    plt.legend()
    plt.tight_layout()
    plt.show()

User Story 3: Current Vs Non Current Liabilities (Investigating the Risk Profile)¶

*Current to Non-Current Liabilities Ratio:**

$$ \text{Current to Non-Current Liabilities Ratio} = \frac{\text{Total Non-Current Liabilities}}{\text{Total Current Liabilities}} $$

Even if the company has enough of assets compared to liability, even if the company is running with the stakeholder's equity. if the company does not have cashflow then the company can suffer day today operations. Higher percentage of short term liabilities (Total current liabilities) can cause suffocation.

Points to note

  • A rise in non-current liabilities might indicate investments in growth projects.
  • A rise in current liabilities might signal short-term borrowing to manage cash flow, which could be a warning sign.

Questions

  1. What percentage of the company's liabilities are due within this year and next years?
  2. Is the company relying too much on short-term debt?
  3. Does the company have a long-term focus with its liabilities?
  4. How does the liability structure vary over time or across companies?
  5. Are there any trends in how the liability structure is shifting (e.g., increasing reliance on short-term debt)?

How can plotting this help us?

  1. A pie chart provides a visual split between short-term (current) and long-term (non-current) obligations. This helps assess how much of the company's liabilities are due soon versus those that are long-term commitments. (Understanding the split)

  2. A higher proportion of current liabilities may indicate a short-term liquidity risk if the company doesn't have sufficient current assets to cover these obligations. Conversely, a high proportion of non-current liabilities may suggest the company is investing in long-term growth or projects but may face debt repayment pressure in the future. (Understanding Risk)

What are we going to Intrepret

  1. Is the company at risk of a cash crunch? A high percentage of current liabilities compared to non-current could be a red flag.

  2. Does the company rely more on short-term or long-term debt? A higher proportion of non-current liabilities might indicate the company is prioritizing long-term financing strategies.

  3. How balanced is the companys liability structure? A good mix of current and non-current liabilities often suggests financial stability.

Columns to consider

  1. totalCurrentLiabilities: Represents liabilities that are due within one year (e.g., accounts payable, short-term debt, etc.).
  2. totalNonCurrentLiabilities: Represents liabilities that are due after one year (e.g., long-term debt, deferred taxes, etc.).
  3. year and Company: If you want to break down the pie chart for each year or company.
In [ ]:
# Get the unique list of companies
companies = df['Company'].unique()

# Loop through each company and create stacked bar charts
for company in companies:
    # Filter data for the current company
    company_data = df[df['Company'] == company]

    # Prepare data for the bar chart
    years = company_data['year'].unique()
    current_liabilities_percentage = []
    non_current_liabilities_percentage = []

    for year in years:
        # Filter data for the specific year
        yearly_data = company_data[company_data['year'] == year]

        # Aggregate current and non-current liabilities
        current_liabilities = yearly_data['totalCurrentLiabilities'].sum()
        non_current_liabilities = yearly_data['totalNonCurrentLiabilities'].sum()
        total_liabilities = current_liabilities + non_current_liabilities

        # Calculate percentages
        current_liabilities_percentage.append((current_liabilities / total_liabilities) * 100)
        non_current_liabilities_percentage.append((non_current_liabilities / total_liabilities) * 100)

    # Plot the stacked bar chart
    plt.figure(figsize=(10, 6))
    plt.bar(years, current_liabilities_percentage, label='Current Liabilities (%)', color='#ff9999')
    plt.bar(years, non_current_liabilities_percentage, bottom=current_liabilities_percentage,
            label='Non-Current Liabilities (%)', color='#66b3ff')

    # Customize the chart
    plt.xlabel('Year')
    plt.ylabel('Percentage (%)')
    plt.title(f'Liability Structure for {company} Over Time')
    plt.legend()

    # Adjust y-axis interval to 10
    plt.gca().yaxis.set_major_locator(mticker.MultipleLocator(10))

    plt.tight_layout()
    plt.show()

Current to Non-Current Liabilities Ratio:

  • Current to Non-Current Liabilities Ratio= current liability /Total non Current Liabilities (aka shortterm./longeterm)

Interpretation:

  1. Ratio < 1: The company has more short-term obligations than long-term obligations. This could indicate reliance on short-term borrowing, which may pose liquidity risks if cash flow is insufficient.

  2. Ratio > 1: The company has more long-term obligations than short-term obligations. This could suggest a focus on long-term financial planning, which might be less risky in the short term but could lead to significant future repayment obligations.

  1. Ratio H 1: The liabilities are evenly distributed, which might suggest balanced financial management.
In [ ]:
df['Current to Non Current Ratio']=df['totalCurrentLiabilities']/df['totalNonCurrentLiabilities']
# Get the unique list of companies
companies = df['Company'].unique()

# Loop through each company and create a line plot for the ratio
for company in companies:
    # Filter data for the current company
    company_data = df[df['Company'] == company]

    # Extract years and the ratio
    years = company_data['year']
    ratio = company_data['Current to Non Current Ratio']

    # Plot the line chart
    plt.figure(figsize=(10, 6))
    plt.plot(years, ratio, marker='o', label='Current to Non-Current Ratio', color='#66b3ff')

    # Add threshold interpretation lines
    plt.axhline(1, color='red', linestyle='--', label='Threshold <=(1: Balanced Liabilities)')

    # Customize the chart
    plt.xlabel('Year')
    plt.ylabel('Ratio')
    plt.title(f'Current to Non-Current Liability Ratio for {company}')
    plt.legend()
    plt.grid(True)
    plt.tight_layout()
    plt.show()
In [ ]:
# Get the unique list of companies
companies = df['Company'].unique()

# Loop through each company and create stacked bar charts for Current Assets vs Current Liabilities
for company in companies:
    # Filter data for the current company
    company_data = df[df['Company'] == company]

    # Extract years, Current Assets, and Current Liabilities
    years = company_data['year']
    current_assets = company_data['totalCurrentAssets']
    current_liabilities = company_data['totalCurrentLiabilities']

    # Calculate percentages
    total_values = current_assets + current_liabilities
    current_assets_percentage = (current_assets / total_values) * 100
    current_liabilities_percentage = (current_liabilities / total_values) * 100

    # Plot the stacked bar chart
    plt.figure(figsize=(10, 6))
    bars1 = plt.bar(years, current_liabilities, label='Current Liabilities (Short-term)', color='#ff9999')
    bars2 = plt.bar(years, current_assets, bottom=current_liabilities, label='Current Assets (Liquidatable)', color='#66b3ff')

    # Annotate percentages on the bars
    for bar1, bar2, ca_percent, cl_percent in zip(bars1, bars2, current_assets_percentage, current_liabilities_percentage):
        # Current Liabilities
        plt.text(bar1.get_x() + bar1.get_width() / 2, bar1.get_height() / 2, f'{cl_percent:.1f}%',
                 ha='center', va='center', color='black', fontsize=9)
        # Current Assets
        plt.text(bar2.get_x() + bar2.get_width() / 2, bar1.get_height() + bar2.get_height() / 2, f'{ca_percent:.1f}%',
                 ha='center', va='center', color='black', fontsize=9)

    # Customize the chart
    plt.xlabel('Year')
    plt.ylabel('Value')
    plt.title(f'Comparison of Current Assets and Liabilities for {company}')
    plt.legend()

User Story 4 : Working Capital Trends (Better understanding of the short term debt)¶

  • how much cash we have to serve our current liabilities (Short term loans)
  • We know that the company is suffering from cash flow problem or not. but lets understand if the company can payoff the short term liability or not (This has a strong co relation with current to non current liability ratio because this ratio tells us if the company suffers cash flow problem or not).

  • Working Capital Trend shows whether the company has enough assets (like cash, receivables, and inventory) to meet short-term liabilities. If working capital is consistently positive, it indicates that the company can sustain its operations without facing immediate financial distress.

  • By tracking working capital over time, you can identify if the company is able to manage short-term liquidity without depending too much on external financing. This helps in strategic decisions like managing cash reserves and short-term debt.

  • Working capital trends can highlight issues such as slow receivables, overstocked inventory, or excessive short-term debt. If the companys working capital is declining due to these factors, operational adjustments (e.g., improving inventory turnover or speeding up receivables collection) can be made.

  • A positive working capital trend may reduce the need for short-term loans or external financing, while a negative trend may signal the need to secure additional financing or improve working capital management. This information is critical for planning funding requirements and avoiding liquidity crises.

  • A growing working capital trend often accompanies revenue growth. This could signal that the company is successfully supporting its growth through its own resources rather than relying heavily on debt or equity financing. It could also indicate that the company is efficiently managing its working capital to support expansion.

Questions to ask

1. Is the company consistently able to meet its short-term financial obligations?

If the working capital trend is positive, it indicates the company has enough current assets (like cash, receivables, inventory) to cover its short-term liabilities. A consistently positive trend suggests a healthy liquidity position.

2. Is there any risk of a cash flow crisis?

If working capital starts decreasing or turns negative, it may signal potential liquidity issues, meaning the company could struggle to pay its short-term obligations without borrowing more or selling assets. It answers the question: Can the company survive short-term financial stress?

3. How efficiently is the company managing its current assets and liabilities?

A trend of increasing working capital can indicate effective management of assets (like receivables and inventory) and liabilities. If the trend is flat or declining, it could point to inefficiencies in managing short-term resources, such as excessive inventory or slow collections.

4. What is the impact of seasonality or cyclical business patterns on liquidity?

If the working capital trend shows cyclical rises and falls, it might indicate seasonality in the business (e.g., retail stores having higher working capital during the holiday season). This helps answer the question: Is the companys liquidity being impacted by seasonal fluctuations?

5. Is the company able to fund its growth using its current assets?

An increasing working capital trend, especially with revenue growth, suggests that the company can finance its expansion without taking on excessive debt or external financing.

Working Capital is calculated as:

$$ \text{Working Capital} = \text{Total Current Assets} - \text{Total Current Liabilities (Short-term Liability)} $$

How to Intrepret

  1. Positive Working Capital Trend: If the working capital trend line is consistently positive or growing, the company is in a good position to meet its obligations and support daily operations. It may indicate effective management of cash flows and a healthy financial position.
  • The company has the resources to continue operations smoothly and can manage unexpected financial stresses. This is a good sign for investors as it suggests low financial risk.
  1. Declining or Negative Working Capital Trend:A downward trend in working capital (especially if it becomes negative) means that the company might not have enough short-term assets to cover its liabilities. This could signal liquidity problems or excessive reliance on debt.
  • The company may be at risk of running into cash flow problems, and without corrective action, it could face difficulties in paying off creditors, which may lead to financial instability. Investors should be cautious in such cases.
  1. Volatility in Working Capital Trend: If the working capital trend fluctuates significantly, it could be due to poor management of cash, inventory, or receivables. Or it could reflect external factors like market conditions or seasonality.
  • High volatility suggests that the companys operations are not stable, and cash flow management is a concern. This is often a red flag for investors who prefer stability in liquidity.
  1. Flat Working Capital Trend:If the trend is flat, it might indicate that the company is neither improving nor worsening its liquidity position. The company may be in a stable state but isnt actively improving its ability to meet short-term obligations.
  • A flat trend suggests no significant risk but also no improvement. For business strategists, this could indicate that its time to optimize operational efficiency or consider new growth strategies.

Columns Required:

  1. Total Current Assets:
  • Column representing the total value of short-term assets, such as cash, accounts receivable, and inventory. Example column name: totalCurrentAssets
  1. Total Current Liabilities (Short-term Liabilities):
  • Column representing the total value of short-term liabilities, such as accounts payable, accrued expenses, and short-term debt. Example column name: totalCurrentLiabilities
  1. Company:
  • To differentiate and analyze working capital trends for individual companies. Example column name: Company
  1. Year:
  • To analyze working capital trends over time.

Working Capital Trend (Line Plot):

Comparison of Current Assets (Total asset that can be liquadated in a year) and current Liabilities( short term liabilities) - Stacked Bar Chart:

  • Foresee how to payoff the current liability using current asset
In [ ]:
# Calculate Working Capital
df['Working Capital'] = df['totalCurrentAssets'] - df['totalCurrentLiabilities']

# Get the unique list of companies
companies = df['Company'].unique()

# Loop through each company and create a line plot for Working Capital trend
for company in companies:
    # Filter data for the current company
    company_data = df[df['Company'] == company]

    # Extract years and Working Capital
    years = company_data['year']
    working_capital = company_data['Working Capital']

    # Plot the line chart
    plt.figure(figsize=(10, 6))
    plt.plot(years, working_capital, marker='o', label='Working Capital', color='#66b3ff')

    # Customize the chart

    plt.xlabel('Year')
    plt.ylabel('Working Capital (Assets - Liabilities)')
    plt.title(f'Working Capital Trend for {company}')
    plt.legend()
    plt.grid(True)
    plt.tight_layout()
    plt.show()

Working Capital vs. Revenue (Bar Plot):

  • Does working capital increase with high revenue?
  • Companies with low working capital but high revenue could be at risk of liquidity issues.
  • Outliers, such as companies with disproportionately low working capital for their revenue, could indicate inefficiencies or high reliance on liabilities.
  • Identifies companies that are over-reliant on credit or underutilizing their assets.
In [ ]:
# Bar Chart: Working Capital vs. Revenue Year-wise for Each Company

# Assuming `df` has the necessary columns: 'Working Capital', 'Revenue', 'Company', and 'year'
# Calculate Working Capital if not already calculated
df['Working Capital'] = df['totalCurrentAssets'] - df['totalCurrentLiabilities']

# Get the unique list of companies
companies = df['Company'].unique()

# Loop through each company and create bar charts
for company in companies:
    # Filter data for the current company
    company_data = df[df['Company'] == company]

    # Extract years, Working Capital, and Revenue
    years = company_data['year']
    working_capital = company_data['Working Capital']
    revenue = company_data['totalRevenue']

    # Plot the bar chart
    plt.figure(figsize=(12, 8))
    bar_width = 0.35
    index = range(len(years))

    # Bars for Working Capital and Revenue
    plt.bar(index, working_capital, bar_width, label='Working Capital', color='#66b3ff')
    plt.bar([i + bar_width for i in index], revenue, bar_width, label='totalRevenue', color='#ff9999')

    # Customize the chart
    plt.xlabel('Year')
    plt.ylabel('Value')
    plt.title(f'Working Capital vs. Revenue Year-wise for {company}')
    plt.xticks([i + bar_width / 2 for i in index], years, rotation=45)
    plt.legend()
    plt.tight_layout()
    plt.grid(axis='y')
    plt.show()
In [ ]:
df.columns
Out[ ]:
Index(['year', 'fiscalDateEnding_balance', 'reportedCurrency_balance',
       'totalAssets', 'totalCurrentAssets',
       'cashAndCashEquivalentsAtCarryingValue', 'cashAndShortTermInvestments',
       'inventory', 'currentNetReceivables', 'totalNonCurrentAssets',
       ...
       'DebtorDays', 'AvgPayables', 'CreditorDays', 'totalDebt',
       'debtRatioToCapital', 'CummulativeCashflowFromOperations',
       'CummulativeCNetProfits', 'Innovation %',
       'Current to Non Current Ratio', 'Working Capital'],
      dtype='object', length=125)

User story 5: P/B Ratio - Find if the company is undervalued or Over valued¶

Low P/B Ratio (< 1): The stock may be undervalued relative to its book value, which could suggest that the market is not giving the company enough credit for its assets or is concerned about future profitability. This could present a potential investment opportunity.

High P/B Ratio (> 1): The stock may be overvalued, indicating that the market is willing to pay more for the companys assets than their book value, which could be a sign of high growth expectations or investor optimism. (Investors believe that company produces more returns with the asset)

P/B Ratio = 1: The market values the company at its book value, i.e., the companys assets are valued exactly as reported.

  • A P/B ratio close to 1 indicates that the market values the company roughly at its book value. This could suggest that the companys assets are being properly utilized and theres a balance between what the company owns (net assets) and how the market values it.

  • A P/B ratio below 1 might indicate that investors believe the companys net assets are worth less than what is reported on the books, potentially due to concerns over financial health, future earnings, or market conditions.

Columns:

  1. P/B Ratio
  2. Year
In [ ]:
# Get the unique list of companies
companies = df['Company'].unique()

# Loop through each company and create trend line charts for P/B Ratio
for company in companies:
    # Filter data for the current company
    company_data = df[df['Company'] == company]

    # Extract years and P/B Ratio
    years = company_data['year']
    pb_ratio = company_data['P/B Ratio']

    # Plot the trend line chart
    plt.figure(figsize=(10, 6))
    plt.plot(years, pb_ratio, marker='o', label='P/B Ratio', color='#66b3ff')

    # Add threshold lines for interpretation
    plt.axhline(1, color='o




























    .


                green ', linestyle='--', label='Ideal Range Start (P/B = 1)')
    plt.axhline(3, color='green', linestyle='--', label='Ideal Range End (P/B = 3)')
    plt.axhline(0.9, color='orange', linestyle='--', label='Undervalued (P/B < 1)')

    # Customize the chart
    plt.xlabel('Year')
    plt.ylabel('P/B Ratio')
    plt.title(f'P/B Ratio Trend for {company}')
    plt.legend()
    plt.grid(True)
    plt.tight_layout()
    plt.show()

Revenue Analysis¶

User story 6: Asset Turnover Ratio - How is the company using its asset to generate revenue?¶

How Can This Help an Investor or Business Strategist?

  1. For Investors:
  • Identify companies that efficiently generate revenue with their assets, leading to better returns on investment.

  • Spot companies with declining trends, signaling potential risks in operational efficiency or asset management.

  1. For Business Strategists:
  • Determine areas of improvement for asset utilization.

  • Decide whether to scale down or invest more in assets based on turnover trends.

  • Evaluate whether fixed assets are contributing adequately to revenue, guiding future capital investment decisions.

Asset Turnover Ratio

$$ \text{Asset Turnover Ratio} = \frac{\text{Revenue (or Total Sales)}}{\text{Total Assets}} $$
  1. Revenue: Represents the total income generated from operations.
  2. Total Assets: Includes both current and non-current assets.

Why do we have this?

Problem it solves:

  • Detects underperformance in utilizing overall assets.

Risk it addresses:

  • Identifies over-investment in low-performing assets, which can lead to inefficiencies and lower returns.

Predictive Insights:

  • Declining trends may indicate operational inefficiency, excess investment in non-revenue-generating assets, or changes in the business model.

Questions we can answer

Operational Efficiency:

  1. How effectively is the company utilizing its assets to generate sales?
  2. Are the assets (fixed and current) underutilized or over-invested?

Growth Opportunities:

  1. Does the company have the capacity to generate more revenue without adding significant assets?
  2. Is there room to improve sales efficiency with the current asset base?

Comparative Performance:

  1. How does the companys asset utilization compare to industry benchmarks or competitors?

Red Flags:

  1. Is a declining ATR a signal of inefficiency or saturation in the companys operations?

Capital Intensity:

  1. How asset-intensive is the business model?
  2. Does the company rely more on a high asset base or operational efficiencies?

Insights:

  • A low ratio suggests the company may not be utilizing its assets effectively or has over-invested in assets.
  • A high ratio indicates efficient use of resources to generate sales.

Columns to plot

  1. Revenue (or Total Sales): totalRevenue
  2. Total Assets: totalAssets
  3. Company: Company
  4. Year: year or derived from fiscalDateEnding_balance.

In short ( Making it simple)

  1. High Asset Turnover Ratio (ATR > 1):
  • If the ATR is high (greater than 1), it means the company is generating more revenue per unit of asset. This implies that the company is effectively utilizing its existing assets, and it may have the capacity to generate additional revenue without needing to significantly increase its assets.

  • Interpretation: If the ATR is improving, the company could potentially scale up its revenue without investing heavily in more assets. This indicates efficient asset utilization, and the company may have room to grow revenue by increasing operational efficiency, rather than just adding new assets.

  1. Low Asset Turnover Ratio (ATR < 1):
  • If the ATR is low, it suggests that the company is not efficiently using its assets to generate revenue. In this case, the company may need to invest more in assets or improve the productivity of its current assets in order to increase revenue.

  • Interpretation: A low ATR implies that there might be underutilized assets or inefficient operations. The company may need to optimize or better utilize its existing asset base to improve revenue generation before considering further investments in assets.

  1. Asset Efficiency & Revenue Generation:
  • Asset Efficiency: A company with a high ATR has optimized its asset base to generate the most revenue possible with the least amount of investment in assets. This means the company can potentially increase revenue by improving operational efficiency, streamlining processes, or maximizing the use of existing assets, rather than acquiring additional assets.

  • Revenue Generation Without Asset Addition: If the ATR is high and stable, it suggests that the company may have the capacity to increase revenue without the need for adding significant assets, as it is already achieving optimal utilization of its current asset base.

In [ ]:
df['Asset Turnover Ratio'] = df['totalRevenue'] / df['totalAssets']

# Get the unique list of companies
companies = df['Company'].unique()

# Loop through each company to create trendline charts
for company in companies:
    # Filter data for the current company
    company_data = df[df['Company'] == company]

    # Extract data for the plot
    years = company_data['year']
    atr = company_data['Asset Turnover Ratio']

    # Plot the ATR trendline
    plt.figure(figsize=(10, 6))
    plt.plot(years, atr, marker='o', color='blue', label='Asset Turnover Ratio (ATR)', linewidth=2)

    # Customize the chart
    plt.xlabel('Year')
    plt.ylabel('Asset Turnover Ratio (ATR)')
    plt.title(f'Asset Turnover Ratio (ATR) Trend for {company}')
    plt.axhline(1, color='green', linestyle='--', label='Threshold (ATR >= 1)')
    plt.grid(True)
    plt.legend()
    plt.tight_layout()
    plt.show()

Return of Assets

$$ \text{ROA} = \frac{\text{Net Income}}{\text{Total Assets}} $$

Questions the plot can answer

Profitability Assessment:

  1. How effectively is the company converting its asset base into profits?
  2. Is the return generated sufficient to justify the investment in assets?

Cost Efficiency:

  1. Is the company managing its operating costs effectively relative to its asset size?

Long-Term Viability:

  1. Is the companys asset portfolio contributing enough to the bottom line to sustain growth?

Investor Insights:

  1. Does the ROA provide a good return on investment for stakeholders?

Business Model Analysis:

  1. Is the companys business model more focused on high-margin, low-turnover assets or high-turnover, low-margin strategies?Profitability Assessment:

  2. How effectively is the company converting its asset base into profits?

  3. Is the return generated sufficient to justify the investment in assets?

Cost Efficiency:

  1. Is the company managing its operating costs effectively relative to its asset size?

Long-Term Viability:

  1. Is the companys asset portfolio contributing enough to the bottom line to sustain growth?

Investor Insights:

  1. Does the ROA provide a good return on investment for stakeholders?

Business Model Analysis:

  1. Is the companys business model more focused on high-margin, low-turnover assets or high-turnover, low-margin strategies?
In [ ]:
# Trendline Chart: Return on Assets (ROA) for Each Company

# Get the unique list of companies
companies = df['Company'].unique()

# Loop through each company to create trendline charts
for company in companies:
    # Filter data for the current company
    company_data = df[df['Company'] == company]

    # Extract data for the plot
    years = company_data['year']
    roa = company_data['ROA']*100

    # Plot the ROA trendline
    plt.figure(figsize=(10, 6))
    plt.plot(years, roa, marker='o', color='blue', label='Return on Assets (ROA)', linewidth=2)

    # Customize the chart
    plt.xlabel('Year')
    plt.ylabel('Return on Assets (ROA)')
    plt.title(f'Return on Assets (ROA) Trend for {company}')
    plt.axhline(0, color='red', linestyle='--', label='>5%')
    plt.grid(True)
    plt.legend()
    plt.tight_layout()
    plt.show()

User Story 7: Gross Profit Margin¶

$$ \text{Gross Profit Margin} = \left( \frac{\text{Gross Profit}}{\text{Revenue}} \right) \times 100 $$
  • Tech Companies (Software, SaaS): GPMs of 70% or higher are common.
  • Retail and Manufacturing: GPMs of 20%-40% are typical.
  • Consumer Goods: GPMs between 30%-50% are usually seen as healthy.
  • Food Industry: GPMs are usually lower, around 15%-25%, due to high production and inventory costs.
In [ ]:
# Calculate Gross Profit Margin (GPM) as a percentage (0 to 100 scale)
df['Gross Profit Margin (%)'] = (df['grossProfit'] / df['totalRevenue']) * 100

# Get the unique list of companies
companies = df['Company'].unique()

# Loop through each company to create GPM percentage line charts
for company in companies:
    # Filter data for the current company
    company_data = df[df['Company'] == company]

    # Extract data for the plot
    years = company_data['year']
    gpm_percentage = company_data['Gross Profit Margin (%)']

    # Plot the GPM percentage line chart
    plt.figure(figsize=(10, 6))
    plt.plot(years, gpm_percentage, marker='o', color='blue', label='Gross Profit Margin (%)', linewidth=2)

    # Customize the chart
    plt.xlabel('Year')
    plt.ylabel('Gross Profit Margin (%)')
    plt.title(f'Gross Profit Margin (GPM) Trend for {company}')

    plt.grid(True)
    plt.legend()
    plt.tight_layout()
    plt.show()

User Story 8 : Operational Profit Margin¶

$$ \text{Operating Profit Margin} = \left( \frac{\text{Operating Profit (EBIT)}}{\text{Revenue}} \right) \times 100 $$
  • Software/Technology: Operating profit margins of 20%-40% or higher are common.
  • Consumer Goods: OPMs can range from 10%-30%.
  • Retail: Typically lower, with OPMs of 5%-10% due to high competition and operational costs.
  • Manufacturing: Similar to retail, operating margins are generally lower, ranging from 5%-15%.
  • Higher Operating Profit Margin: Indicates that the company is good at converting revenue into operating profit, showing operational efficiency. This suggests effective cost control and good management.

  • Lower Operating Profit Margin: Can indicate poor cost management, low pricing power, or higher operational expenses that need to be addressed.

  • Trend Analysis: A growing operating profit margin is positive, indicating improved efficiency or profitability from core operations. A declining margin may require further investigation into cost structure or business model changes.

Columns

  1. Operating Profit: EBIT
  2. Revenue: totalRevenue
In [ ]:
# Calculate Operating Profit Margin (OPM) as a percentage (0 to 100 scale)
df['Operating Profit Margin (%)'] = (df['ebit'] / df['totalRevenue']) * 100

# Get the unique list of companies
companies = df['Company'].unique()

# Loop through each company to create OPM percentage line charts
for company in companies:
    # Filter data for the current company
    company_data = df[df['Company'] == company]

    # Extract data for the plot
    years = company_data['year']
    opm_percentage = company_data['Operating Profit Margin (%)']

    # Plot the OPM percentage line chart
    plt.figure(figsize=(10, 6))
    plt.plot(years, opm_percentage, marker='o', color='blue', label='Operating Profit Margin (%)', linewidth=2)

    # Customize the chart
    plt.xlabel('Year')
    plt.ylabel('Operating Profit Margin (%)')
    plt.title(f'Operating Profit Margin (OPM) Trend for {company}')
    plt.grid(True)
    plt.legend()
    plt.tight_layout()
    plt.show()

User story 9 : Net Profit Margin (NPM) - How profitable is the company after accounting for all expenses and taxes?¶

$$ \text{Net Profit Margin (NPM)} = \left( \frac{\text{Net Income}}{\text{Total Revenue}} \right) \times 100 $$
  • Higher values indicate strong profitability; declining trends may signal inefficiencies.
  • Measures how much net profit a company makes for every dollar of revenue.
  • Helps evaluate overall profitability and efficiency in controlling costs.
  • Indicates how well the company converts revenue into profit.
  • Typically >10% for strong companies, but varies by industry
In [ ]:
# Calculate Net Profit Margin (NPM) as a percentage (0 to 100 scale)
df['Net Profit Margin (%)'] = (df['netIncome'] / df['totalRevenue']) * 100
# Get the unique list of companies
companies = df['Company'].unique()

# Loop through each company to create NPM percentage line charts
for company in companies:
    # Filter data for the current company
    company_data = df[df['Company'] == company]

    # Extract data for the plot
    years = company_data['year']
    npm_percentage = company_data['Net Profit Margin (%)']

    # Plot the NPM percentage line chart
    plt.figure(figsize=(10, 6))
    plt.plot(years, npm_percentage, marker='o', color='blue', label='Net Profit Margin (%)', linewidth=2)

    # Customize the chart
    plt.xlabel('Year')
    plt.ylabel('Net Profit Margin (%)')
    plt.title(f'Net Profit Margin (NPM) Trend for {company}')
    plt.grid(True)
    plt.legend()
    plt.tight_layout()
    plt.show()

User story 10: Operating Income Ratio (EBIT Margin) - Is the company's core business efficiently generating profit?¶

  • Measures the operating profit relative to revenue, excluding non-operational expenses.
  • Focuses on core business profitability before accounting for interest and taxes.
  • Shows operational efficiency and health of core business.
  • A rising trend suggests operational improvements, while a falling trend indicates challenges in controlling costs.
$$ \text{Percentage} = \left( \frac{\text{Operating Income (EBIT)}}{\text{Total Revenue}} \right) \times 100 $$

Varies; >15% is generally good for many industries.

In [ ]:
# Calculate Operating Income Ratio (EBIT Margin) as a percentage
df['Operating Income Ratio (EBIT Margin) (%)'] = (df['ebit'] / df['totalRevenue']) * 100

# Get the unique list of companies
companies = df['Company'].unique()

# Loop through each company to create Operating Income Ratio trend line charts
for company in companies:
    # Filter data for the current company
    company_data = df[df['Company'] == company]

    # Extract data for the plot
    years = company_data['year']
    ebit_margin = company_data['Operating Income Ratio (EBIT Margin) (%)']

    # Plot the Operating Income Ratio trend line chart
    plt.figure(figsize=(10, 6))
    plt.plot(years, ebit_margin, marker='o', color='blue', label='Operating Income Ratio (%)', linewidth=2)

    # Customize the chart
    plt.xlabel('Year')
    plt.ylabel('Operating Income Ratio (%)')
    plt.title(f'Operating Income Ratio (EBIT Margin) Trend for {company}')
    plt.grid(True)
    plt.legend()
    plt.tight_layout()
    plt.show()

User story 11: P/S - Is the company's stock valued appropriately relative to its sales?¶

  • Compares the company's market value to its total revenue.
  • Helps assess if the stock is overvalued or undervalued relative to sales.
  • Useful for evaluating growth companies with little or no profit.
$$ \text{Ratio} = \frac{\text{Market Capitalization}}{\text{Total Revenue}} $$
  • Varies by industry; typically 1-3 is considered good.
  • Lower values suggest undervaluation; higher values may indicate optimism or overvaluation.
In [ ]:
# Get the unique list of companies
companies = df['Company'].unique()

# Loop through each company to create EPS trend line charts
for company in companies:
    # Filter data for the current company
    company_data = df[df['Company'] == company]

    # Extract data for the plot
    years = company_data['year']
    ps_ratio = company_data['P/S Ratio']

    # Plot the EPS trend line chart
    plt.figure(figsize=(10, 6))
    plt.plot(years, ps_ratio, marker='o', color='blue', label='P/S Ratio', linewidth=2)
    plt.axhline(1, color='green', linestyle='--', label='Threshold(1-3)')

    # Customize the chart
    plt.xlabel('Year')
    plt.ylabel('P/S ratio')
    plt.title(f'P/S Ratio Trend for {company}')
    plt.grid(True)
    plt.legend()
    plt.tight_layout()
    plt.show()

User story 12: Earnings Per Share (EPS) - How much profit is attributable to each share of stock??¶

  • Represents the portion of a company's profit allocated to each outstanding share of common stock.
  • Indicates a companys profitability on a per-share basis.
  • A key metric for comparing profitability across companies.
$$ \text{EPS} = \frac{\text{Net Income}}{\text{Common Stock Shares Outstanding}} $$
  • Higher is better; varies widely by industry and company size.
  • Rising EPS trends indicate improving profitability, while falling EPS suggests challenges.
In [ ]:
# Get the unique list of companies
companies = df['Company'].unique()

# Loop through each company to create EPS trend line charts
for company in companies:
    # Filter data for the current company
    company_data = df[df['Company'] == company]

    # Extract data for the plot
    years = company_data['year']
    eps = company_data['EPS']

    # Plot the EPS trend line chart
    plt.figure(figsize=(10, 6))
    plt.plot(years, eps, marker='o', color='blue', label='Earnings Per Share (EPS)', linewidth=2)

    # Customize the chart
    plt.xlabel('Year')
    plt.ylabel('Earnings Per Share (EPS)')
    plt.title(f'Earnings Per Share (EPS) Trend for {company}')
    plt.grid(True)
    plt.legend()
    plt.tight_layout()
    plt.show()

Userstory 13 : Price-to-Earnings (P/E) Ratio - Is the company’s stock price justified by its earnings?¶

  • Compares a company's share price to its earnings per share.
  • Helps determine if a stock is overvalued or undervalued based on current earnings.
  • Assesses market expectations of future growth.
$$ \text{P/E Ratio} = \frac{\text{Market Price per Share}}{\text{Earnings Per Share (EPS)}} $$
  • 15-25 is typical; high-growth industries can have higher ratios.
  • High values may indicate overvaluation, while low values can signal undervaluation or financial challenges.
In [ ]:
# Normalize the industry average P/E dictionary keys to uppercase
industry_average_pe = {
    "META": 26.16,
    "APPLE": 34.82,
    "SNAPCHAT": 31.35,
    "MICROSOFT": 34.55,
    "GOOGLE": 22.24
}

# Normalize company names in the dataset
df['Company'] = df['Company'].str.upper()

# Get the unique list of companies
companies = df['Company'].unique()

# Loop through each company to create P/E Ratio trend line charts with company-specific thresholds
for company in companies:
    # Filter data for the current company
    company_data = df[df['Company'] == company]

    # Extract data for the plot
    years = company_data['year']
    pe_ratio = company_data['P/E Ratio']

    # Retrieve the industry average for the current company
    avg_pe = industry_average_pe.get(company, None)
    if avg_pe is None:
        print(f"No industry average available for {company}. Skipping...")
        continue

    # Plot the P/E Ratio trend line chart
    plt.figure(figsize=(10, 6))
    plt.plot(years, pe_ratio, marker='o', color='blue', label='P/E Ratio', linewidth=2)

    # Add thresholds based on industry average
    plt.axhline(avg_pe, color='green', linestyle='--', label=f'Industry Average P/E ({avg_pe:.2f})')

    # Customize the chart
    plt.xlabel('Year')
    plt.ylabel('P/E Ratio')
    plt.title(f'Price-to-Earnings (P/E) Ratio Trend for {company}')
    plt.grid(True)
    plt.legend()
    plt.tight_layout()
    plt.show()

CASH FLOW ANALYSIS¶

User Story 14 : # Operating Cash Flow Ratio (Can the company meet its short-term obligations with cash generated from operations?)¶

$$ \text{Ratio} = \frac{\text{Operating Cash Flow}}{\text{Total Current Liabilities}} $$
  • Indicates whether the company can pay off short-term liabilities using cash from operations.
  • ">1"
  • A higher ratio means better liquidity and operational efficiency.
In [ ]:
# Calculate Operating Cash Flow Ratio
df['Operating Cash Flow Ratio'] = df['operatingCashflow'] / df['totalCurrentLiabilities']
# Get the unique list of companies
companies = df['Company'].unique()

# Loop through each company to create Operating Cash Flow Ratio trend line charts
for company in companies:
    # Filter data for the current company
    company_data = df[df['Company'] == company]

    # Extract data for the plot
    years = company_data['year']
    ocf_ratio = company_data['Operating Cash Flow Ratio']

    # Plot the Operating Cash Flow Ratio trend line chart
    plt.figure(figsize=(10, 6))
    plt.plot(years, ocf_ratio, marker='o', color='blue', label='Operating Cash Flow Ratio', linewidth=2)

    # Customize the chart
    plt.xlabel('Year')
    plt.ylabel('Operating Cash Flow Ratio')
    plt.title(f'Operating Cash Flow Ratio Trend for {company}')
    plt.grid(True)
    plt.legend()
    plt.tight_layout()
    plt.show()

User Story 15:Cash Flow to Debt Ratio (How effectively can the company pay off its debt using operational cash?)¶

$$ \text{Ratio} = \frac{\text{Operating Cash Flow}}{\text{Total Current Liabilities}+{Total Non Current Liabilities}} $$
  • Evaluates the ability to repay debts using operating cash flow.
  • Helps investors assess the companys financial risk and ability to handle debt.
  • Higher is better (varies).
  • A higher ratio indicates stronger debt repayment capacity; lower values signal risk.
In [ ]:
# Calculate Cash Flow to Debt Ratio
df['Cash Flow to Debt Ratio'] = df['operatingCashflow'] / (df['totalCurrentLiabilities'] + df['totalNonCurrentLiabilities'])

# Get the unique list of companies
companies = df['Company'].unique()

# Loop through each company to create Cash Flow to Debt Ratio trend line charts
for company in companies:
    # Filter data for the current company
    company_data = df[df['Company'] == company]

    # Extract data for the plot
    years = company_data['year']
    cash_flow_debt_ratio = company_data['Cash Flow to Debt Ratio']

    # Plot the Cash Flow to Debt Ratio trend line chart
    plt.figure(figsize=(10, 6))
    plt.plot(years, cash_flow_debt_ratio, marker='o', color='blue', label='Cash Flow to Debt Ratio', linewidth=2)

    # Customize the chart
    plt.xlabel('Year')
    plt.ylabel('Cash Flow to Debt Ratio')
    plt.title(f'Cash Flow to Debt Ratio Trend for {company}')
    plt.grid(True)
    plt.legend()
    plt.tight_layout()
    plt.show()

User Story 16: Capital Expenditure Ratio¶

$$ \text{Ratio} = \frac{\text{Operating Cash Flow}}{\text{Capital Expenditures}} $$
  • Indicates whether the company can fund investments from its operations.
  • Shows if the company is self-sufficient in funding asset growth without relying on debt or external funding.
  • ">1"
  • Higher values indicate the company has enough operational cash to reinvest in its growth.
  • Can the company afford its capital investments without taking on debt?
In [ ]:
# Calculate Capital Expenditure Ratio
df['Capital Expenditure Ratio'] = df['operatingCashflow'] / df['capitalExpenditures']

# Get the unique list of companies
companies = df['Company'].unique()

# Loop through each company to create Capital Expenditure Ratio trend line charts
for company in companies:
    # Filter data for the current company
    company_data = df[df['Company'] == company]

    # Extract data for the plot
    years = company_data['year']
    capex_ratio = company_data['Capital Expenditure Ratio']

    # Plot the Capital Expenditure Ratio trend line chart
    plt.figure(figsize=(10, 6))
    plt.plot(years, capex_ratio, marker='o', color='blue', label='Capital Expenditure Ratio', linewidth=2)

    # Customize the chart
    plt.xlabel('Year')
    plt.ylabel('Capital Expenditure Ratio')
    plt.title(f'Capital Expenditure Ratio Trend for {company}')
    plt.grid(True)
    plt.legend()
    plt.tight_layout()
    plt.show()

User Story 17: Free Cash Flow (FCF) - How much cash is left after operational and investment expenses? Can the company fund dividends or reduce debt?¶

$$ \text{Result} = \text{Operating Cash Flow} - \text{Capital Expenditures} $$
  • Measures cash available after capital investments.
  • Indicates financial flexibility for dividends, debt repayment, or reinvestment opportunities.
  • Positive value is ideal.
  • Positive FCF means financial stability; negative values suggest over-reliance on external funding.
In [ ]:
# Calculate Free Cash Flow (FCF)
df['Free Cash Flow'] = df['operatingCashflow'] - df['capitalExpenditures']

# Get the unique list of companies
companies = df['Company'].unique()

# Loop through each company to create Free Cash Flow trend line charts
for company in companies:
    # Filter data for the current company
    company_data = df[df['Company'] == company]

    # Extract data for the plot
    years = company_data['year']
    fcf = company_data['Free Cash Flow']

    # Plot the Free Cash Flow trend line chart
    plt.figure(figsize=(10, 6))
    plt.plot(years, fcf, marker='o', color='blue', label='Free Cash Flow (FCF)', linewidth=2)

    # Customize the chart
    plt.xlabel('Year')
    plt.ylabel('Free Cash Flow (FCF)')
    plt.title(f'Free Cash Flow (FCF) Trend for {company}')
    plt.grid(True)
    plt.legend()
    plt.tight_layout()
    plt.show()

User Story 18 : Cash Flow Margin Ratio (How efficiently is the company converting revenue into cash flow?)¶

$$ \text{Percentage} = \left( \frac{\text{Operating Cash Flow}}{\text{Total Revenue}} \right) \times 100 $$
  • Shows operational efficiency in converting revenue into cash.
  • Helps investors understand how much of the revenue turns into cash that can be used for operations or reinvestment.
  • Higher is better (varies).
  • A higher ratio reflects better cash conversion efficiency; a lower ratio points to inefficiencies in cash management.
In [ ]:
# Calculate Cash Flow Margin Ratio as a percentage
df['Cash Flow Margin Ratio (%)'] = (df['operatingCashflow'] / df['totalRevenue']) * 100

# Get the unique list of companies
companies = df['Company'].unique()

# Loop through each company to create Cash Flow Margin Ratio trend line charts
for company in companies:
    # Filter data for the current company
    company_data = df[df['Company'] == company]

    # Extract data for the plot
    years = company_data['year']
    cash_flow_margin = company_data['Cash Flow Margin Ratio (%)']

    # Plot the Cash Flow Margin Ratio trend line chart
    plt.figure(figsize=(10, 6))
    plt.plot(years, cash_flow_margin, marker='o', color='blue', label='Cash Flow Margin Ratio (%)', linewidth=2)

    # Customize the chart
    plt.xlabel('Year')
    plt.ylabel('Cash Flow Margin Ratio (%)')
    plt.title(f'Cash Flow Margin Ratio Trend for {company}')
    plt.grid(True)
    plt.legend()
    plt.tight_layout()
    plt.show()

User Story 19 :Dividend Payout Ratio (Cash-Based) - Are the company’s dividends sustainable? Does the company retain enough cash for growth and obligations?¶

$$ \text{Ratio} = \frac{\text{Dividend Payout}}{\text{Operating Cash Flow}} $$
  • Shows the proportion of cash flow allocated to shareholder dividends.
  • Indicates dividend sustainability and the companys financial discipline in rewarding shareholders.
  • < 50% is ideal.
  • A low ratio indicates sustainable dividend payouts; higher values may suggest cash constraints for reinvestments or debts.
In [ ]:
# Fill null values in 'Dividend Payout' column with 0
df['dividendPayout'] = df['dividendPayout'].fillna(0)

# Calculate Dividend Payout Ratio (Cash-Based)
df['Dividend Payout Ratio (Cash-Based)'] = df['dividendPayout'] / df['operatingCashflow']

# Get the unique list of companies
companies = df['Company'].unique()

# Loop through each company to create Dividend Payout Ratio trend line charts
for company in companies:
    # Filter data for the current company
    company_data = df[df['Company'] == company]

    # Extract data for the plot
    years = company_data['year']
    dividend_payout_ratio = company_data['Dividend Payout Ratio (Cash-Based)']

    # Plot the Dividend Payout Ratio trend line chart
    plt.figure(figsize=(10, 6))
    plt.plot(years, dividend_payout_ratio, marker='o', color='blue', label='Dividend Payout Ratio (Cash-Based)', linewidth=2)

    # Customize the chart
    plt.xlabel('Year')
    plt.ylabel('Dividend Payout Ratio')
    plt.title(f'Dividend Payout Ratio Trend for {company}')
    plt.grid(True)
    plt.legend()
    plt.tight_layout()
    plt.show()

User Story 20 : Short-Term Debt Coverage - Can the company settle its short-term debt (Not the Total current liability) obligations without liquidity issues?(Need to verify if the calculation is done properly)¶

$$ \text{Ratio} = \frac{\text{Operating Cash Flow}}{\text{Short-Term Debt}} $$
  • Measures the companys ability to pay short-term borrowings.
  • Helps assess liquidity risks and short-term solvency of the company.
  • "> 1"
  • A higher ratio means better capability to settle short-term debts using operational cash.
In [ ]:
# Calculate Short-Term Debt Coverage Ratio
df['operatingCashflow'].fillna(0)
df['shortTermDebt'].fillna(0)
df['Short-Term Debt Coverage Ratio'] = df['operatingCashflow'] / df['shortTermDebt']
# Get the unique list of companies
companies = df['Company'].unique()

# Loop through each company to create Short-Term Debt Coverage Ratio trend line charts
for company in companies:
    # Filter data for the current company
    company_data = df[df['Company'] == company]

    # Extract data for the plot
    years = company_data['year']
    short_term_debt_coverage = company_data['Short-Term Debt Coverage Ratio']

    # Plot the Short-Term Debt Coverage Ratio trend line chart
    plt.figure(figsize=(10, 6))
    plt.plot(years, short_term_debt_coverage, marker='o', color='blue', label='Short-Term Debt Coverage Ratio', linewidth=2)

    # Customize the chart
    plt.xlabel('Year')
    plt.ylabel('Short-Term Debt Coverage Ratio')
    plt.title(f'Short-Term Debt Coverage Ratio Trend for {company}')
    plt.grid(True)
    plt.legend()
    plt.tight_layout()
    plt.show()

User Story 21 : Cash Flow Adequacy Ratio (Can the company cover its capital investments, debt repayments, and dividend payments using operational cash?)¶

$$ \text{Ratio} = \frac{\text{Operating Cash Flow}}{\text{Capital Expenditures} + \text{Short-Term Debt} + \text{Dividend Payout}} $$
  • Evaluates if cash flow covers essential obligations.
  • Indicates financial flexibility to handle operational, debt, and dividend commitments.
  • "> 1"
  • A ratio above 1 indicates that the company generates enough cash to cover essential expenses; below 1 signals financial stress.
In [ ]:
# Fill null values in the relevant columns with 0
df['Operating Cash Flow'] = df['operatingCashflow'].fillna(0)
df['Capital Expenditures'] = df['capitalExpenditures'].fillna(0)
df['Short-Term Debt'] = df['shortTermDebt'].fillna(0)
df['Dividend Payout'] = df['dividendPayout'].fillna(0)

# Recalculate Cash Flow Adequacy Ratio
df['Cash Flow Adequacy Ratio'] = df['Operating Cash Flow'] / (
    df['Capital Expenditures'] + df['Short-Term Debt'] + df['Dividend Payout']
)

# Get the unique list of companies
companies = df['Company'].unique()

# Loop through each company to create Cash Flow Adequacy Ratio trend line charts
for company in companies:
    # Filter data for the current company
    company_data = df[df['Company'] == company]

    # Extract data for the plot
    years = company_data['year']
    cash_flow_adequacy = company_data['Cash Flow Adequacy Ratio']

    # Plot the Cash Flow Adequacy Ratio trend line chart
    plt.figure(figsize=(10, 6))
    plt.plot(years, cash_flow_adequacy, marker='o', color='blue', label='Cash Flow Adequacy Ratio', linewidth=2)

    # Customize the chart
    plt.xlabel('Year')
    plt.ylabel('Cash Flow Adequacy Ratio')
    plt.title(f'Cash Flow Adequacy Ratio Trend for {company}')
    plt.grid(True)
    plt.legend()
    plt.tight_layout()
    plt.show()
In [ ]: